Evaluating the impact of odors from the 1955 landfills in China using a bottom-up approach
Landfill odors have created a major concern for the Chinese public. Based on the combination of a first order decay (FOD) model and a ground-level point source Gaussian dispersion model, the impacts from odors emitted from the 1955 landfills in China are evaluated in this paper. Our bottom-up approa...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Cai, Bofeng [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2015transfer abstract |
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| Schlagwörter: |
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| Umfang: |
9 |
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| Übergeordnetes Werk: |
Enthalten in: Cohort, signaling, and early-career dynamics: The hidden significance of class in black-white earnings inequality - Ren, Chunhui ELSEVIER, 2022, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:164 ; year:2015 ; day:1 ; month:12 ; pages:206-214 ; extent:9 |
| Links: |
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| DOI / URN: |
10.1016/j.jenvman.2015.09.009 |
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| 245 | 1 | 0 | |a Evaluating the impact of odors from the 1955 landfills in China using a bottom-up approach |
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| 520 | |a Landfill odors have created a major concern for the Chinese public. Based on the combination of a first order decay (FOD) model and a ground-level point source Gaussian dispersion model, the impacts from odors emitted from the 1955 landfills in China are evaluated in this paper. Our bottom-up approach uses basic data related to each landfill to achieve a more accurate and comprehensive understanding of impact of landfill odors. Results reveal that the average radius of impact of landfill odors in China is 796 m, while most landfills (46.85%) are within the range of 400–1000 m, in line with the results from previous studies. The total land area impacted by odors has reached 837,476 ha, accounting for 0.09% of China's land territory. Guangdong and Sichuan provinces have the largest land areas impacted by odors, while Tibet Autonomous Region and Tianjin Municipality have the smallest. According to the CALPUFF (California Puff) model and an analysis of social big data, the overall uncertainty of our calculation of the range of odor impacts is roughly −32.88% to 32.67%. This type of study is essential for gaining an accurate and detailed estimation of the affected human population and will prove valuable for addressing the current Not In My Back Yard (NIMBY) challenge in China. | ||
| 520 | |a Landfill odors have created a major concern for the Chinese public. Based on the combination of a first order decay (FOD) model and a ground-level point source Gaussian dispersion model, the impacts from odors emitted from the 1955 landfills in China are evaluated in this paper. Our bottom-up approach uses basic data related to each landfill to achieve a more accurate and comprehensive understanding of impact of landfill odors. Results reveal that the average radius of impact of landfill odors in China is 796 m, while most landfills (46.85%) are within the range of 400–1000 m, in line with the results from previous studies. The total land area impacted by odors has reached 837,476 ha, accounting for 0.09% of China's land territory. Guangdong and Sichuan provinces have the largest land areas impacted by odors, while Tibet Autonomous Region and Tianjin Municipality have the smallest. According to the CALPUFF (California Puff) model and an analysis of social big data, the overall uncertainty of our calculation of the range of odor impacts is roughly −32.88% to 32.67%. This type of study is essential for gaining an accurate and detailed estimation of the affected human population and will prove valuable for addressing the current Not In My Back Yard (NIMBY) challenge in China. | ||
| 650 | 7 | |a Odor impact ranges |2 Elsevier | |
| 650 | 7 | |a Landfill |2 Elsevier | |
| 650 | 7 | |a Bottom-up |2 Elsevier | |
| 650 | 7 | |a Uncertainty evaluation |2 Elsevier | |
| 700 | 1 | |a Wang, Jinnan |4 oth | |
| 700 | 1 | |a Long, Ying |4 oth | |
| 700 | 1 | |a Li, Wanxin |4 oth | |
| 700 | 1 | |a Liu, Jianguo |4 oth | |
| 700 | 1 | |a Ni, Zhe |4 oth | |
| 700 | 1 | |a Bo, Xin |4 oth | |
| 700 | 1 | |a Li, Dong |4 oth | |
| 700 | 1 | |a Wang, Jianghao |4 oth | |
| 700 | 1 | |a Chen, Xuejing |4 oth | |
| 700 | 1 | |a Gao, Qingxian |4 oth | |
| 700 | 1 | |a Zhang, Lixiao |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Elsevier |a Ren, Chunhui ELSEVIER |t Cohort, signaling, and early-career dynamics: The hidden significance of class in black-white earnings inequality |d 2022 |g Amsterdam [u.a.] |w (DE-627)ELV008002754 |
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10.1016/j.jenvman.2015.09.009 doi GBVA2015010000001.pica (DE-627)ELV018497780 (ELSEVIER)S0301-4797(15)30261-9 DE-627 ger DE-627 rakwb eng 333.7 690 333.7 DNB 690 DNB 300 VZ 70.00 bkl 71.00 bkl Cai, Bofeng verfasserin aut Evaluating the impact of odors from the 1955 landfills in China using a bottom-up approach 2015transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Landfill odors have created a major concern for the Chinese public. Based on the combination of a first order decay (FOD) model and a ground-level point source Gaussian dispersion model, the impacts from odors emitted from the 1955 landfills in China are evaluated in this paper. Our bottom-up approach uses basic data related to each landfill to achieve a more accurate and comprehensive understanding of impact of landfill odors. Results reveal that the average radius of impact of landfill odors in China is 796 m, while most landfills (46.85%) are within the range of 400–1000 m, in line with the results from previous studies. The total land area impacted by odors has reached 837,476 ha, accounting for 0.09% of China's land territory. Guangdong and Sichuan provinces have the largest land areas impacted by odors, while Tibet Autonomous Region and Tianjin Municipality have the smallest. According to the CALPUFF (California Puff) model and an analysis of social big data, the overall uncertainty of our calculation of the range of odor impacts is roughly −32.88% to 32.67%. This type of study is essential for gaining an accurate and detailed estimation of the affected human population and will prove valuable for addressing the current Not In My Back Yard (NIMBY) challenge in China. Landfill odors have created a major concern for the Chinese public. Based on the combination of a first order decay (FOD) model and a ground-level point source Gaussian dispersion model, the impacts from odors emitted from the 1955 landfills in China are evaluated in this paper. Our bottom-up approach uses basic data related to each landfill to achieve a more accurate and comprehensive understanding of impact of landfill odors. Results reveal that the average radius of impact of landfill odors in China is 796 m, while most landfills (46.85%) are within the range of 400–1000 m, in line with the results from previous studies. The total land area impacted by odors has reached 837,476 ha, accounting for 0.09% of China's land territory. Guangdong and Sichuan provinces have the largest land areas impacted by odors, while Tibet Autonomous Region and Tianjin Municipality have the smallest. According to the CALPUFF (California Puff) model and an analysis of social big data, the overall uncertainty of our calculation of the range of odor impacts is roughly −32.88% to 32.67%. This type of study is essential for gaining an accurate and detailed estimation of the affected human population and will prove valuable for addressing the current Not In My Back Yard (NIMBY) challenge in China. Odor impact ranges Elsevier Landfill Elsevier Bottom-up Elsevier Uncertainty evaluation Elsevier Wang, Jinnan oth Long, Ying oth Li, Wanxin oth Liu, Jianguo oth Ni, Zhe oth Bo, Xin oth Li, Dong oth Wang, Jianghao oth Chen, Xuejing oth Gao, Qingxian oth Zhang, Lixiao oth Enthalten in Elsevier Ren, Chunhui ELSEVIER Cohort, signaling, and early-career dynamics: The hidden significance of class in black-white earnings inequality 2022 Amsterdam [u.a.] (DE-627)ELV008002754 volume:164 year:2015 day:1 month:12 pages:206-214 extent:9 https://doi.org/10.1016/j.jenvman.2015.09.009 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 70.00 Sozialwissenschaften allgemein: Allgemeines VZ 71.00 Soziologie: Allgemeines VZ AR 164 2015 1 1201 206-214 9 045F 333.7 |
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10.1016/j.jenvman.2015.09.009 doi GBVA2015010000001.pica (DE-627)ELV018497780 (ELSEVIER)S0301-4797(15)30261-9 DE-627 ger DE-627 rakwb eng 333.7 690 333.7 DNB 690 DNB 300 VZ 70.00 bkl 71.00 bkl Cai, Bofeng verfasserin aut Evaluating the impact of odors from the 1955 landfills in China using a bottom-up approach 2015transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Landfill odors have created a major concern for the Chinese public. Based on the combination of a first order decay (FOD) model and a ground-level point source Gaussian dispersion model, the impacts from odors emitted from the 1955 landfills in China are evaluated in this paper. Our bottom-up approach uses basic data related to each landfill to achieve a more accurate and comprehensive understanding of impact of landfill odors. Results reveal that the average radius of impact of landfill odors in China is 796 m, while most landfills (46.85%) are within the range of 400–1000 m, in line with the results from previous studies. The total land area impacted by odors has reached 837,476 ha, accounting for 0.09% of China's land territory. Guangdong and Sichuan provinces have the largest land areas impacted by odors, while Tibet Autonomous Region and Tianjin Municipality have the smallest. According to the CALPUFF (California Puff) model and an analysis of social big data, the overall uncertainty of our calculation of the range of odor impacts is roughly −32.88% to 32.67%. This type of study is essential for gaining an accurate and detailed estimation of the affected human population and will prove valuable for addressing the current Not In My Back Yard (NIMBY) challenge in China. Landfill odors have created a major concern for the Chinese public. Based on the combination of a first order decay (FOD) model and a ground-level point source Gaussian dispersion model, the impacts from odors emitted from the 1955 landfills in China are evaluated in this paper. Our bottom-up approach uses basic data related to each landfill to achieve a more accurate and comprehensive understanding of impact of landfill odors. Results reveal that the average radius of impact of landfill odors in China is 796 m, while most landfills (46.85%) are within the range of 400–1000 m, in line with the results from previous studies. The total land area impacted by odors has reached 837,476 ha, accounting for 0.09% of China's land territory. Guangdong and Sichuan provinces have the largest land areas impacted by odors, while Tibet Autonomous Region and Tianjin Municipality have the smallest. According to the CALPUFF (California Puff) model and an analysis of social big data, the overall uncertainty of our calculation of the range of odor impacts is roughly −32.88% to 32.67%. This type of study is essential for gaining an accurate and detailed estimation of the affected human population and will prove valuable for addressing the current Not In My Back Yard (NIMBY) challenge in China. Odor impact ranges Elsevier Landfill Elsevier Bottom-up Elsevier Uncertainty evaluation Elsevier Wang, Jinnan oth Long, Ying oth Li, Wanxin oth Liu, Jianguo oth Ni, Zhe oth Bo, Xin oth Li, Dong oth Wang, Jianghao oth Chen, Xuejing oth Gao, Qingxian oth Zhang, Lixiao oth Enthalten in Elsevier Ren, Chunhui ELSEVIER Cohort, signaling, and early-career dynamics: The hidden significance of class in black-white earnings inequality 2022 Amsterdam [u.a.] (DE-627)ELV008002754 volume:164 year:2015 day:1 month:12 pages:206-214 extent:9 https://doi.org/10.1016/j.jenvman.2015.09.009 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 70.00 Sozialwissenschaften allgemein: Allgemeines VZ 71.00 Soziologie: Allgemeines VZ AR 164 2015 1 1201 206-214 9 045F 333.7 |
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10.1016/j.jenvman.2015.09.009 doi GBVA2015010000001.pica (DE-627)ELV018497780 (ELSEVIER)S0301-4797(15)30261-9 DE-627 ger DE-627 rakwb eng 333.7 690 333.7 DNB 690 DNB 300 VZ 70.00 bkl 71.00 bkl Cai, Bofeng verfasserin aut Evaluating the impact of odors from the 1955 landfills in China using a bottom-up approach 2015transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Landfill odors have created a major concern for the Chinese public. Based on the combination of a first order decay (FOD) model and a ground-level point source Gaussian dispersion model, the impacts from odors emitted from the 1955 landfills in China are evaluated in this paper. Our bottom-up approach uses basic data related to each landfill to achieve a more accurate and comprehensive understanding of impact of landfill odors. Results reveal that the average radius of impact of landfill odors in China is 796 m, while most landfills (46.85%) are within the range of 400–1000 m, in line with the results from previous studies. The total land area impacted by odors has reached 837,476 ha, accounting for 0.09% of China's land territory. Guangdong and Sichuan provinces have the largest land areas impacted by odors, while Tibet Autonomous Region and Tianjin Municipality have the smallest. According to the CALPUFF (California Puff) model and an analysis of social big data, the overall uncertainty of our calculation of the range of odor impacts is roughly −32.88% to 32.67%. This type of study is essential for gaining an accurate and detailed estimation of the affected human population and will prove valuable for addressing the current Not In My Back Yard (NIMBY) challenge in China. Landfill odors have created a major concern for the Chinese public. Based on the combination of a first order decay (FOD) model and a ground-level point source Gaussian dispersion model, the impacts from odors emitted from the 1955 landfills in China are evaluated in this paper. Our bottom-up approach uses basic data related to each landfill to achieve a more accurate and comprehensive understanding of impact of landfill odors. Results reveal that the average radius of impact of landfill odors in China is 796 m, while most landfills (46.85%) are within the range of 400–1000 m, in line with the results from previous studies. The total land area impacted by odors has reached 837,476 ha, accounting for 0.09% of China's land territory. Guangdong and Sichuan provinces have the largest land areas impacted by odors, while Tibet Autonomous Region and Tianjin Municipality have the smallest. According to the CALPUFF (California Puff) model and an analysis of social big data, the overall uncertainty of our calculation of the range of odor impacts is roughly −32.88% to 32.67%. This type of study is essential for gaining an accurate and detailed estimation of the affected human population and will prove valuable for addressing the current Not In My Back Yard (NIMBY) challenge in China. Odor impact ranges Elsevier Landfill Elsevier Bottom-up Elsevier Uncertainty evaluation Elsevier Wang, Jinnan oth Long, Ying oth Li, Wanxin oth Liu, Jianguo oth Ni, Zhe oth Bo, Xin oth Li, Dong oth Wang, Jianghao oth Chen, Xuejing oth Gao, Qingxian oth Zhang, Lixiao oth Enthalten in Elsevier Ren, Chunhui ELSEVIER Cohort, signaling, and early-career dynamics: The hidden significance of class in black-white earnings inequality 2022 Amsterdam [u.a.] (DE-627)ELV008002754 volume:164 year:2015 day:1 month:12 pages:206-214 extent:9 https://doi.org/10.1016/j.jenvman.2015.09.009 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 70.00 Sozialwissenschaften allgemein: Allgemeines VZ 71.00 Soziologie: Allgemeines VZ AR 164 2015 1 1201 206-214 9 045F 333.7 |
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10.1016/j.jenvman.2015.09.009 doi GBVA2015010000001.pica (DE-627)ELV018497780 (ELSEVIER)S0301-4797(15)30261-9 DE-627 ger DE-627 rakwb eng 333.7 690 333.7 DNB 690 DNB 300 VZ 70.00 bkl 71.00 bkl Cai, Bofeng verfasserin aut Evaluating the impact of odors from the 1955 landfills in China using a bottom-up approach 2015transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Landfill odors have created a major concern for the Chinese public. Based on the combination of a first order decay (FOD) model and a ground-level point source Gaussian dispersion model, the impacts from odors emitted from the 1955 landfills in China are evaluated in this paper. Our bottom-up approach uses basic data related to each landfill to achieve a more accurate and comprehensive understanding of impact of landfill odors. Results reveal that the average radius of impact of landfill odors in China is 796 m, while most landfills (46.85%) are within the range of 400–1000 m, in line with the results from previous studies. The total land area impacted by odors has reached 837,476 ha, accounting for 0.09% of China's land territory. Guangdong and Sichuan provinces have the largest land areas impacted by odors, while Tibet Autonomous Region and Tianjin Municipality have the smallest. According to the CALPUFF (California Puff) model and an analysis of social big data, the overall uncertainty of our calculation of the range of odor impacts is roughly −32.88% to 32.67%. This type of study is essential for gaining an accurate and detailed estimation of the affected human population and will prove valuable for addressing the current Not In My Back Yard (NIMBY) challenge in China. Landfill odors have created a major concern for the Chinese public. Based on the combination of a first order decay (FOD) model and a ground-level point source Gaussian dispersion model, the impacts from odors emitted from the 1955 landfills in China are evaluated in this paper. Our bottom-up approach uses basic data related to each landfill to achieve a more accurate and comprehensive understanding of impact of landfill odors. Results reveal that the average radius of impact of landfill odors in China is 796 m, while most landfills (46.85%) are within the range of 400–1000 m, in line with the results from previous studies. The total land area impacted by odors has reached 837,476 ha, accounting for 0.09% of China's land territory. Guangdong and Sichuan provinces have the largest land areas impacted by odors, while Tibet Autonomous Region and Tianjin Municipality have the smallest. According to the CALPUFF (California Puff) model and an analysis of social big data, the overall uncertainty of our calculation of the range of odor impacts is roughly −32.88% to 32.67%. This type of study is essential for gaining an accurate and detailed estimation of the affected human population and will prove valuable for addressing the current Not In My Back Yard (NIMBY) challenge in China. Odor impact ranges Elsevier Landfill Elsevier Bottom-up Elsevier Uncertainty evaluation Elsevier Wang, Jinnan oth Long, Ying oth Li, Wanxin oth Liu, Jianguo oth Ni, Zhe oth Bo, Xin oth Li, Dong oth Wang, Jianghao oth Chen, Xuejing oth Gao, Qingxian oth Zhang, Lixiao oth Enthalten in Elsevier Ren, Chunhui ELSEVIER Cohort, signaling, and early-career dynamics: The hidden significance of class in black-white earnings inequality 2022 Amsterdam [u.a.] (DE-627)ELV008002754 volume:164 year:2015 day:1 month:12 pages:206-214 extent:9 https://doi.org/10.1016/j.jenvman.2015.09.009 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 70.00 Sozialwissenschaften allgemein: Allgemeines VZ 71.00 Soziologie: Allgemeines VZ AR 164 2015 1 1201 206-214 9 045F 333.7 |
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10.1016/j.jenvman.2015.09.009 doi GBVA2015010000001.pica (DE-627)ELV018497780 (ELSEVIER)S0301-4797(15)30261-9 DE-627 ger DE-627 rakwb eng 333.7 690 333.7 DNB 690 DNB 300 VZ 70.00 bkl 71.00 bkl Cai, Bofeng verfasserin aut Evaluating the impact of odors from the 1955 landfills in China using a bottom-up approach 2015transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Landfill odors have created a major concern for the Chinese public. Based on the combination of a first order decay (FOD) model and a ground-level point source Gaussian dispersion model, the impacts from odors emitted from the 1955 landfills in China are evaluated in this paper. Our bottom-up approach uses basic data related to each landfill to achieve a more accurate and comprehensive understanding of impact of landfill odors. Results reveal that the average radius of impact of landfill odors in China is 796 m, while most landfills (46.85%) are within the range of 400–1000 m, in line with the results from previous studies. The total land area impacted by odors has reached 837,476 ha, accounting for 0.09% of China's land territory. Guangdong and Sichuan provinces have the largest land areas impacted by odors, while Tibet Autonomous Region and Tianjin Municipality have the smallest. According to the CALPUFF (California Puff) model and an analysis of social big data, the overall uncertainty of our calculation of the range of odor impacts is roughly −32.88% to 32.67%. This type of study is essential for gaining an accurate and detailed estimation of the affected human population and will prove valuable for addressing the current Not In My Back Yard (NIMBY) challenge in China. Landfill odors have created a major concern for the Chinese public. Based on the combination of a first order decay (FOD) model and a ground-level point source Gaussian dispersion model, the impacts from odors emitted from the 1955 landfills in China are evaluated in this paper. Our bottom-up approach uses basic data related to each landfill to achieve a more accurate and comprehensive understanding of impact of landfill odors. Results reveal that the average radius of impact of landfill odors in China is 796 m, while most landfills (46.85%) are within the range of 400–1000 m, in line with the results from previous studies. The total land area impacted by odors has reached 837,476 ha, accounting for 0.09% of China's land territory. Guangdong and Sichuan provinces have the largest land areas impacted by odors, while Tibet Autonomous Region and Tianjin Municipality have the smallest. According to the CALPUFF (California Puff) model and an analysis of social big data, the overall uncertainty of our calculation of the range of odor impacts is roughly −32.88% to 32.67%. This type of study is essential for gaining an accurate and detailed estimation of the affected human population and will prove valuable for addressing the current Not In My Back Yard (NIMBY) challenge in China. Odor impact ranges Elsevier Landfill Elsevier Bottom-up Elsevier Uncertainty evaluation Elsevier Wang, Jinnan oth Long, Ying oth Li, Wanxin oth Liu, Jianguo oth Ni, Zhe oth Bo, Xin oth Li, Dong oth Wang, Jianghao oth Chen, Xuejing oth Gao, Qingxian oth Zhang, Lixiao oth Enthalten in Elsevier Ren, Chunhui ELSEVIER Cohort, signaling, and early-career dynamics: The hidden significance of class in black-white earnings inequality 2022 Amsterdam [u.a.] (DE-627)ELV008002754 volume:164 year:2015 day:1 month:12 pages:206-214 extent:9 https://doi.org/10.1016/j.jenvman.2015.09.009 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 70.00 Sozialwissenschaften allgemein: Allgemeines VZ 71.00 Soziologie: Allgemeines VZ AR 164 2015 1 1201 206-214 9 045F 333.7 |
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evaluating the impact of odors from the 1955 landfills in china using a bottom-up approach |
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Evaluating the impact of odors from the 1955 landfills in China using a bottom-up approach |
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Landfill odors have created a major concern for the Chinese public. Based on the combination of a first order decay (FOD) model and a ground-level point source Gaussian dispersion model, the impacts from odors emitted from the 1955 landfills in China are evaluated in this paper. Our bottom-up approach uses basic data related to each landfill to achieve a more accurate and comprehensive understanding of impact of landfill odors. Results reveal that the average radius of impact of landfill odors in China is 796 m, while most landfills (46.85%) are within the range of 400–1000 m, in line with the results from previous studies. The total land area impacted by odors has reached 837,476 ha, accounting for 0.09% of China's land territory. Guangdong and Sichuan provinces have the largest land areas impacted by odors, while Tibet Autonomous Region and Tianjin Municipality have the smallest. According to the CALPUFF (California Puff) model and an analysis of social big data, the overall uncertainty of our calculation of the range of odor impacts is roughly −32.88% to 32.67%. This type of study is essential for gaining an accurate and detailed estimation of the affected human population and will prove valuable for addressing the current Not In My Back Yard (NIMBY) challenge in China. |
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Landfill odors have created a major concern for the Chinese public. Based on the combination of a first order decay (FOD) model and a ground-level point source Gaussian dispersion model, the impacts from odors emitted from the 1955 landfills in China are evaluated in this paper. Our bottom-up approach uses basic data related to each landfill to achieve a more accurate and comprehensive understanding of impact of landfill odors. Results reveal that the average radius of impact of landfill odors in China is 796 m, while most landfills (46.85%) are within the range of 400–1000 m, in line with the results from previous studies. The total land area impacted by odors has reached 837,476 ha, accounting for 0.09% of China's land territory. Guangdong and Sichuan provinces have the largest land areas impacted by odors, while Tibet Autonomous Region and Tianjin Municipality have the smallest. According to the CALPUFF (California Puff) model and an analysis of social big data, the overall uncertainty of our calculation of the range of odor impacts is roughly −32.88% to 32.67%. This type of study is essential for gaining an accurate and detailed estimation of the affected human population and will prove valuable for addressing the current Not In My Back Yard (NIMBY) challenge in China. |
| abstract_unstemmed |
Landfill odors have created a major concern for the Chinese public. Based on the combination of a first order decay (FOD) model and a ground-level point source Gaussian dispersion model, the impacts from odors emitted from the 1955 landfills in China are evaluated in this paper. Our bottom-up approach uses basic data related to each landfill to achieve a more accurate and comprehensive understanding of impact of landfill odors. Results reveal that the average radius of impact of landfill odors in China is 796 m, while most landfills (46.85%) are within the range of 400–1000 m, in line with the results from previous studies. The total land area impacted by odors has reached 837,476 ha, accounting for 0.09% of China's land territory. Guangdong and Sichuan provinces have the largest land areas impacted by odors, while Tibet Autonomous Region and Tianjin Municipality have the smallest. According to the CALPUFF (California Puff) model and an analysis of social big data, the overall uncertainty of our calculation of the range of odor impacts is roughly −32.88% to 32.67%. This type of study is essential for gaining an accurate and detailed estimation of the affected human population and will prove valuable for addressing the current Not In My Back Yard (NIMBY) challenge in China. |
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According to the CALPUFF (California Puff) model and an analysis of social big data, the overall uncertainty of our calculation of the range of odor impacts is roughly −32.88% to 32.67%. This type of study is essential for gaining an accurate and detailed estimation of the affected human population and will prove valuable for addressing the current Not In My Back Yard (NIMBY) challenge in China.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Landfill odors have created a major concern for the Chinese public. Based on the combination of a first order decay (FOD) model and a ground-level point source Gaussian dispersion model, the impacts from odors emitted from the 1955 landfills in China are evaluated in this paper. Our bottom-up approach uses basic data related to each landfill to achieve a more accurate and comprehensive understanding of impact of landfill odors. Results reveal that the average radius of impact of landfill odors in China is 796 m, while most landfills (46.85%) are within the range of 400–1000 m, in line with the results from previous studies. The total land area impacted by odors has reached 837,476 ha, accounting for 0.09% of China's land territory. Guangdong and Sichuan provinces have the largest land areas impacted by odors, while Tibet Autonomous Region and Tianjin Municipality have the smallest. According to the CALPUFF (California Puff) model and an analysis of social big data, the overall uncertainty of our calculation of the range of odor impacts is roughly −32.88% to 32.67%. This type of study is essential for gaining an accurate and detailed estimation of the affected human population and will prove valuable for addressing the current Not In My Back Yard (NIMBY) challenge in China.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Odor impact ranges</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Landfill</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Bottom-up</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Uncertainty evaluation</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wang, Jinnan</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Long, Ying</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Li, Wanxin</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Liu, Jianguo</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ni, Zhe</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Bo, Xin</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Li, Dong</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wang, Jianghao</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Chen, Xuejing</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Gao, Qingxian</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhang, Lixiao</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier</subfield><subfield code="a">Ren, Chunhui ELSEVIER</subfield><subfield code="t">Cohort, signaling, and early-career dynamics: The hidden significance of class in black-white earnings inequality</subfield><subfield code="d">2022</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV008002754</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:164</subfield><subfield code="g">year:2015</subfield><subfield code="g">day:1</subfield><subfield code="g">month:12</subfield><subfield code="g">pages:206-214</subfield><subfield code="g">extent:9</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.jenvman.2015.09.009</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">70.00</subfield><subfield code="j">Sozialwissenschaften allgemein: Allgemeines</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">71.00</subfield><subfield code="j">Soziologie: Allgemeines</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">164</subfield><subfield code="j">2015</subfield><subfield code="b">1</subfield><subfield code="c">1201</subfield><subfield code="h">206-214</subfield><subfield code="g">9</subfield></datafield><datafield tag="953" ind1=" " ind2=" "><subfield code="2">045F</subfield><subfield code="a">333.7</subfield></datafield></record></collection>
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