1
|
Wang Y, Hu L, Hou L, Cai W, He Y, Su X. Study on Carbon Emission Influencing Factors and carbon emission reduction potential in China's food production industry. ENVIRONMENTAL RESEARCH 2024; 261:119702. [PMID: 39094894 DOI: 10.1016/j.envres.2024.119702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Revised: 06/30/2024] [Accepted: 07/27/2024] [Indexed: 08/04/2024]
Abstract
Climate warming has become a global issue of close concern, and China, as a significant agricultural country, has an increasing demand for food, which requires China to increase carbon reduction in this industry. This paper accounts for carbon emissions from the food production industry (CEFI) using the input-output method, then screens the influencing factors of CEFI based on Random Forest (RF), analyzes the heterogeneous effects of the influencing factors on CEFI in different clusters through K-means-SHAP, and finally explores the potential of carbon emissions from this industry for the period 2024-2040. The study's findings are as follows: First, there are apparent inequalities in CEFI, especially between provinces, which are gradually increasing. Second, addressing people's consumption awareness and behaviors is not the fundamental solution to alleviate CEFI; instead, it should focus on sustainable agricultural production transformation and "food miles" in the transportation phase. In addition, attention needs to be paid to the impacts of fertilizer application, transport modes, and livestock management on the CEFI of each cluster. Finally, the study suggests that around 2028, 70% of China's provinces will be at the "carbon peak" and that less developed and more developed regions have more significant potential to reduce emissions. In this regard, this paper encourages a series of policies that are key to promoting the sustainable development of CEFI, such as reducing the volume and efficiency of traditional fertilizers, vigorously developing organic fertilizer inputs, strengthening technological innovation and R&D inputs in the transportation sector, and steadily supporting germplasm innovation in the livestock sector.
Collapse
Affiliation(s)
- Yuanping Wang
- School of Civil Engineering and Architecture, Chongqing University of Science and Technology, Chongqing 401331, China.
| | - Lang Hu
- School of Civil Engineering and Architecture, Chongqing University of Science and Technology, Chongqing 401331, China.
| | - Lingchun Hou
- School of Construction Management and Real Estate, Chongqing University, Chongqing 40044, China.
| | - Weiguang Cai
- School of Construction Management and Real Estate, Chongqing University, Chongqing 40044, China.
| | - Yu He
- School of Civil Engineering and Architecture, Chongqing University of Science and Technology, Chongqing 401331, China.
| | - Xinyue Su
- School of Civil Engineering and Architecture, Chongqing University of Science and Technology, Chongqing 401331, China.
| |
Collapse
|
2
|
Wang F, Liu S, Liu H, Zhao Y, Dong Y, Tran LSP, Li W. Resilience assessment of the nitrogen flow system in food production and consumption for sustainable development on the Qinghai-Tibet Plateau. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 896:165223. [PMID: 37392886 DOI: 10.1016/j.scitotenv.2023.165223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 06/27/2023] [Accepted: 06/28/2023] [Indexed: 07/03/2023]
Abstract
A robust and resilient nitrogen (N) flow system can effectively ensure consistent food production and consumption activities while preserving environmental quality. In this study, we constructed an indicator system to evaluate N flow system resilience including food production and consumption, at the county scale on the Qinghai-Tibet Plateau (QTP) from 1998 to 2018. The subsystem coupling coordination degree (CCD) and the effect of N losses on N flow system resilience were subsequently explored. The results indicated that despite the overall N flow system resilience remaining low and exhibiting spatiotemporal disparities from 1998 to 2018, over 90 % of the counties experienced improvements. High resilience areas (>0.15) were mainly concentrated in some counties in Sichuan Province, where N losses were positively correlated with system resilience. The level of resilience depended on agricultural and livestock development, and the CCD of subsystems was also high (>0.5) in this region, with the most balanced environmental and socioeconomic development. The low system resilience areas were concentrated in the eastern part of the QTP, where human activities caused substantial disturbances. The fragmentation of the agro-pastoral system coupled with the low system resilience of the food production and driving pressure subsystems led to low CCD between subsystems. In contrast, the western regions, characterized by a stable food production system, high food self-sufficiency, and weak dependence on external systems, showed a higher degree of system resilience and resistance. Our findings provide a reference for N resource management and policy formulation for food production and consumption in the agricultural and pastoral areas of the QTP.
Collapse
Affiliation(s)
- Fangfang Wang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Shiliang Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China.
| | - Hua Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Yifei Zhao
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Yuhong Dong
- Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China
| | - Lam-Son Phan Tran
- Institute of Genomics for Crop Abiotic Stress Tolerance, Department of Plant and Soil Science, Texas Tech University, Lubbock, TX 79409, USA
| | - Weiqiang Li
- Key Laboratory of Mollisols Agroecology, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China
| |
Collapse
|
3
|
Wang F, Liu S, Liu Y, Yu L, Wang Q, Liu H, Dong Y, Sun J. Food Nitrogen Footprint Increased by 35% on the Third Pole During 1998-2018. GEOHEALTH 2023; 7:e2022GH000737. [PMID: 36852182 PMCID: PMC9958206 DOI: 10.1029/2022gh000737] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 01/02/2023] [Accepted: 01/27/2023] [Indexed: 06/18/2023]
Abstract
The N footprint is considered as an indicator of potential environmental damage from N. Quantitative analysis of N footprint distribution, sources and drivers can help mitigate its negative impacts and promote sustainable N management. In this study, we constructed a city-scale food N footprint (FNF) framework for the Qinghai-Tibet Plateau (QTP) using a N mass balance approach. We quantitatively analyzed the FNF during food production and consumption on the QTP from 1998 to 2018. We used the logarithmic mean Divisa index decomposition method to analyze the driving forces of the FNF, and the decoupling of the FNF. The results showed that the per capita FNF of the QTP increased from 24.92 kg N cap-1 in 1998 to 27.70 kg N cap-1 in 2018, and the total FNF increased by 35.11% from 1998 to 2018. The spatial distribution of the FNF was uneven, with N losses from crop production and animal production being the leading contributing source to the FNF (86%). Economic development and urbanization were the main driving forces behind the FNF increase, while N consumption intensity inhibited the growth of the FNF. With the rapid growth of GDP, the FNF in the eastern part of the QTP grew relatively slowly, indicating a gradual decoupling of the FNF from economic development. To reconcile the relationship between socioeconomic drivers and the FNF, it is necessary to focus on coupling relationships between subsystems within the food production and consumption system to promote N recycling.
Collapse
Affiliation(s)
- Fangfang Wang
- State Key Laboratory of Water Environment SimulationSchool of EnvironmentBeijing Normal UniversityBeijingChina
| | - Shiliang Liu
- State Key Laboratory of Water Environment SimulationSchool of EnvironmentBeijing Normal UniversityBeijingChina
| | - Yixuan Liu
- State Key Laboratory of Water Environment SimulationSchool of EnvironmentBeijing Normal UniversityBeijingChina
| | - Lu Yu
- State Key Laboratory of Water Environment SimulationSchool of EnvironmentBeijing Normal UniversityBeijingChina
| | - Qingbo Wang
- State Key Laboratory of Water Environment SimulationSchool of EnvironmentBeijing Normal UniversityBeijingChina
| | - Hua Liu
- State Key Laboratory of Water Environment SimulationSchool of EnvironmentBeijing Normal UniversityBeijingChina
| | - Yuhong Dong
- Research Institute of ForestryChinese Academy of ForestryBeijingChina
| | - Jian Sun
- Institute of Tibetan Plateau ResearchChinese Academy of SciencesBeijingChina
| |
Collapse
|
4
|
Li X, Li Y, Zhao S, Chen X, Wang L, Zhang X. Early cognitive dysfunction after stroke and related risk factors in the high-altitude and multi-ethnic region of Qinghai, China: A multi-center cross-sectional study. Clin Neurol Neurosurg 2023; 225:107607. [PMID: 36696845 DOI: 10.1016/j.clineuro.2023.107607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 12/28/2022] [Accepted: 12/30/2022] [Indexed: 01/21/2023]
Abstract
OBJECTIVE Cognitive impairment is a common outcome of stroke, but there is limited evidence regarding its prevalence at high altitude, especially within the context of specific ethnic groups or lifestyle habits. This prospective exploratory study investigated early cognitive impairment after stroke in Qinghai Province, 3000 m above sea level. METHODS Patients with acute stroke (n = 1047) were enrolled from 3 hospitals in Qinghai Province. Cognitive performance was measured by Montreal Cognitive Assessment (MoCA) scores within 5 days of stroke symptom onset; MoCA < 26 defined impairment. Patient data included demographics, education, vascular risk factors, diet, and activities of daily living rated by Barthel index. RESULTS Cognitive impairment within 5 days of stroke symptom onset affected 77.65% of these patients. The factors independently associated with early cognitive impairment were: older age (mean difference [MD]: -4.857, 95% confidence interval [CI]: 6.685-3.030, P < 0.001); female gender (odds ratio [OR]: 1.674, 95% CI: 1.212-2.313, P = 0.002); and a diet containing yak butter (OR: 1.587, 95% CI: 1.247-2.021, P < 0.001). Progressively lesser odds were accounted to beef (Yak) and mutton consumption (OR: 0.804, 95% CI: 0.655-0.987, P = 0.037); fruit (OR: 0.792, 95% CI: 0.672-0.933, P = 0.005); status as an immigrant (OR: 0.666, 95% CI: 0.445-0.996, P = 0.048); education (OR: 0.514, 95% CI: 0.400-0.660, P < 0.001); and multiple daily leisure activities (OR: 0.999, 95% CI: 0.999-0.999, P < 0.001). CONCLUSION Persons in Qinghai province who experience stroke are likely to show signs of early cognitive dysfunction. Preventive modifiable features include diet and daily activities.
Collapse
Affiliation(s)
- Xiaofang Li
- Qinghai Provincial People's Hospital, Xining 81007, China
| | - Yuemei Li
- Qinghai Provincial People's Hospital, Xining 81007, China
| | - Shengxiu Zhao
- Qinghai Provincial People's Hospital, Xining 81007, China.
| | | | - Limei Wang
- Third People's Hospital of Xining, Xining 81000, China
| | - Xiaoxia Zhang
- Qinghai Provincial People's Hospital, Xining 81007, China
| |
Collapse
|
5
|
Wang F, Liu S, Liu H, Liu Y, Yu L, Wang Q, Dong Y, Sun J, Tran LSP, Li W. Aggravation of nitrogen losses driven by agriculture and livestock farming development on the Qinghai-Tibet Plateau. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 326:116795. [PMID: 36442330 DOI: 10.1016/j.jenvman.2022.116795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 11/06/2022] [Accepted: 11/12/2022] [Indexed: 06/16/2023]
Abstract
Nitrogen (N) losses from crop-livestock production is a major threat to the environment and human health at regional, national and global scales. A comprehensive understanding of the sources, spatiotemporal distribution and drivers of N losses is of great significance for mitigating its negative impacts and promoting N sustainable management. Here, we used the county-scale N flow model to quantitatively analyze the N losses and their driving forces of crop-livestock production on the Qinghai-Tibet Plateau (QTP). Between 2000 and 2018, the total N losses increased for more than 79% of counties on the QTP. The hotspot areas accounted for over 80% of total N losses, expanding from the east and south to the north and west of the QTP. NH3 was the main source of atmospheric N losses (over 80%) while the direct discharge of manure was the main source of water N losses. Structural equation modeling (SEM) showed that chemical fertilizer caused the largest driving effect on atmospheric N losses, and the total output value of agriculture and forestry was the main driver of water N losses. Uneven distribution of crop production and livestock contributed to the aggravation of N losses. Over 70% of counties had grater manure N excretion than crops could take up, and large proportion of manure could not be returned to the field. More than 90% of the counties used grater amount of chemical fertilizer N than crops could take up, indicating that livestock manure has not yet fully replaced chemical fertilizer N. The results provide effective guidance and support for N utilization and management of livestock in agricultural and pastoral areas.
Collapse
Affiliation(s)
- Fangfang Wang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, 100875, China.
| | - Shiliang Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, 100875, China.
| | - Hua Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, 100875, China
| | - Yixuan Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, 100875, China
| | - Lu Yu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, 100875, China
| | - Qingbo Wang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, 100875, China
| | - Yuhong Dong
- Research Institute of Forestry, Chinese Academy of Forestry, Beijing, 100091, China
| | - Jian Sun
- Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, 100101, China
| | - Lam-Son Phan Tran
- Institute of Genomics for Crop Abiotic Stress Tolerance, Department of Plant and Soil Science, Texas Tech University, Lubbock, TX, 79409, USA; Institute of Research and Development, Duy Tan University, Da Nang, 550000, Viet Nam
| | - Weiqiang Li
- Key Laboratory of Mollisols Agroecology, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
| |
Collapse
|
6
|
Wang F, Liu S, Liu H, Liu Y, Yu L, Wang Q, Dong Y, Tran LSP, Sun J, Zhao W. Scenarios and sustainability of the economy-nitrogen-resource-environment system using a system dynamic model on the Qinghai-Tibet Plateau. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022; 318:115623. [PMID: 35777154 DOI: 10.1016/j.jenvman.2022.115623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 05/12/2022] [Accepted: 06/23/2022] [Indexed: 06/15/2023]
Abstract
Nitrogen (N) plays a vital role in the development of crop production and animal husbandry in agricultural and pastoral areas. However, the irrational utilization of N resources and subsequent environmental issues with rapid economic development has attracted wide public attention. Coordinating the economy-N-resource-environment (ENRE) system is of great importance for regional sustainable development. In this study, the dynamics of the ENRE system of a typical agricultural and pastoral area on the Qinghai-Tibet Plateau (QTP) were simulated using the VENSIM software from 1998 to 2018. Four typical scenarios (current development scenario, economic development scenario, environment protection scenario and resource optimization scenario) are established to assess the sustainability level and the coupling coordination degrees (CCDs) of the three subsystems, i.e., the economy, N-resource and environment subsystems from 2019 to 2030. Our study indicates that the N flow-based system dynamics (SD) model connects the different subsystems of the ENRE system together well and allows different scenario simulations. From 2019 to 2030, the ENRE system is at a weak sustainability level during the simulation period, and the three subsystems are at slightly unbalanced stages of development in terms of CCD level. The sustainability and CCD levels of the four examined scenarios are as follows: resource optimization scenario > economic development scenario > environment protection scenario >current development scenario, with average values of 0.45, 0.37; 0.42, 0.36; 0.41, 0.35; and 0.39, 0.34, respectively. Under the resource optimization scenario, reducing N inputs to food production and consumption and reducing the planting area of cash crops can effectively improve the N use efficiency of the food chain in the N-resource subsystem (15.34% from 2019 to 2030 on average). Our results provide a reference for promoting sustainable development and formulating policies in agricultural and pastoral regions.
Collapse
Affiliation(s)
- Fangfang Wang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, 100875, China
| | - Shiliang Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, 100875, China.
| | - Hua Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, 100875, China
| | - Yixuan Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, 100875, China
| | - Lu Yu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, 100875, China
| | - Qingbo Wang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, 100875, China
| | - Yuhong Dong
- Research Institute of Forestry, Chinese Academy of Forestry, Beijing, 100091, China
| | - Lam-Son Phan Tran
- Institute of Genomics for Crop Abiotic Stress Tolerance, Department of Plant and Soil Science, Texas Tech University, Lubbock, TX, 79409, USA
| | - Jian Sun
- Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, 100101, China
| | - Wenwu Zhao
- Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China
| |
Collapse
|