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Akyuz E, Cingiroglu F, Kaynak B, Unal A. A bottom-up agricultural emissions inventory and its analysis via CMAQ and IASI-NH 3. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 950:175355. [PMID: 39122047 DOI: 10.1016/j.scitotenv.2024.175355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/21/2024] [Revised: 07/23/2024] [Accepted: 08/05/2024] [Indexed: 08/12/2024]
Abstract
The global increase in population has led to higher emissions from livestock and synthetic fertilizers. This study investigates the impact of agricultural ammonia emissions on NH3 concentrations and provides insights into PM2.5 levels and their components in agriculturally intensified areas. We developed a bottom-up emission inventory focused on fertilizer application over croplands and livestock, instead of relying on the EMEP database. This approach utilized an improved spatial and temporal distribution of these emissions. We compared annual total NH3 emissions from livestock and fertilizer, estimated at 598.5 kt and 187.2 kt in the EMEP inventory (Base case), and 245.2 kt and 536 kt in the bottom-up inventory (Scenario case). Using the CMAQ modelling framework, we estimated atmospheric concentrations for both cases and evaluated the model results by comparing them with IASI-NH3 satellite retrievals. This comparison revealed significant differences in column concentrations between the Base and Scenario cases, with the Scenario case showing substantial improvement. Over a period of seven months, which contributed 80 % of the annual agricultural emissions for the Scenario case, the domain averages of NH3 were 3.02 × 1015, 4.15 × 1015, and 4.17 × 1015 molecules/cm2 for the Base and Scenario cases and IASI-NH3, respectively. The Scenario case closely matched IASI measurements, indicating a more accurate representation of NH3 emissions and concentrations. This enhanced reliability underscores the effectiveness of the bottom-up inventory approach. Additionally, using the CMAQ model, we found that in the IASI hotspots, the averages were 1.67 μg/m3 for sulfate, 0.57 μg/m3 for nitrate, and 0.62 μg/m3 for ammonium, with a total PM2.5 mean of 10.45 μg/m3.
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Affiliation(s)
- Ezgi Akyuz
- Eurasia Institute of Earth Sciences, Istanbul Technical University, Istanbul, Turkey
| | - Fulya Cingiroglu
- Eurasia Institute of Earth Sciences, Istanbul Technical University, Istanbul, Turkey
| | - Burcak Kaynak
- School of Civil Engineering, Department of Environmental Engineering, Istanbul Technical University, Istanbul, Turkey
| | - Alper Unal
- Eurasia Institute of Earth Sciences, Istanbul Technical University, Istanbul, Turkey; Civil and Environmental Engineering, University of Washington, Seattle, United States of America
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Chen P, Wang Q, Shao M, Liu R. Significantly underestimated traffic-related ammonia emissions in Chinese megacities: Evidence from satellite observations during COVID-19 lockdowns. CHEMOSPHERE 2024; 361:142497. [PMID: 38825248 DOI: 10.1016/j.chemosphere.2024.142497] [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: 02/21/2024] [Revised: 05/28/2024] [Accepted: 05/30/2024] [Indexed: 06/04/2024]
Abstract
Ammonia (NH3) plays an important role in the formation of atmospheric particulate matter, but the contribution of traffic-related emissions remains unclear, particularly in megacities with a large number of vehicles. Taking the opportunity of the stringent COVID-19 lockdowns implemented in Beijing and Shanghai in 2022, this study aims to estimate the traffic-related NH3 emissions in these two megacities based on satellite observations. Differences between urban and suburban areas during the lockdown and non-lockdown periods are compared. It was found that despite different dominating sources, the overall NH3 concentrations in urban and suburban areas were at a similar level, and the lockdown resulted in a more prominent decrease in urban areas, where traffic activities were most heavily affected. The traffic-related contribution to the total emission was estimated to be ∼30% in megacities, and ∼40% in urban areas, which are about 2-10 times higher than that in previous studies. The findings indicate that the traffic-related NH3 emissions have been significantly underestimated in previous studies and may play a more critical role in the formation of air pollution in megacities, especially in winter, when agricultural emissions are relatively low. This study highlights the importance of traffic-related NH3 emissions in Chinese megacities and the need to reassess the emissions and their impacts on air quality.
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Affiliation(s)
- Peilin Chen
- State Key Laboratory of Pollution Control and Resources Reuse, School of the Environment, Nanjing University, Nanjing, 210023, China
| | - Qin'geng Wang
- State Key Laboratory of Pollution Control and Resources Reuse, School of the Environment, Nanjing University, Nanjing, 210023, China; Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing, 210044, China.
| | - Min Shao
- School of the Environment, Nanjing Normal University, Nanjing, 210046, China
| | - Rui Liu
- State Key Laboratory of Pollution Control and Resources Reuse, School of the Environment, Nanjing University, Nanjing, 210023, China
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Xu L, Bao Y, Man H, Zhang Z, Chen J, Shao X, Zhu B, Liu H. Influencing factors on ammonia emissions from gasoline vehicles: A systematic review and meta-analysis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 923:171467. [PMID: 38447721 DOI: 10.1016/j.scitotenv.2024.171467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 02/18/2024] [Accepted: 03/02/2024] [Indexed: 03/08/2024]
Abstract
Ammonia, a significant precursor for secondary inorganic aerosols, plays a pivotal role in new particle formation. Inventories and source apportionment studies have identified vehicular exhaust as a primary source of atmospheric ammonia in urban regions. Existing research on the factors influencing ammonia emissions from gasoline vehicles exhibits substantial inconsistencies in both test results and analyses. The lack of a uniform pattern in ammonia emissions across different standard vehicles and the significant overlap in test results across diverse operational conditions highlight the complexities in this field of study. While individual results can be interpreted through a mechanistic lens, disparate studies often lack a common explanatory framework. To address this gap, our study leverages the robust and comprehensive approach of meta-analysis to reconcile these inconsistencies and provide a more precise understanding of the factors influencing ammonia emissions from gasoline vehicles. A large number (N = 537) of ammonia emission factors were extracted after screening >1628 publications. The combined ammonia emission factor was 23.57 ± 24.94 mg/km. Emission standards, engine type, ambient temperatures, mileage, vehicle speed, and engine displacement have a significant impact on ammonia emission factors, explaining the ammonia emission factor by up to 50.63 %, with speed being the most significant factor. All these factors are attributed to the interplay of catalyst properties, lambda, and residence time (space velocity). In the current fleet, ammonia emission control is relatively insufficient under low-speed and ultra-high speed, low temperature, and ultra-high mileage conditions. Since ammonia emission factors do not monotonically decrease with the upgrading of motor vehicle emission standards, it is called for the addition of ammonia emission factors indicators in motor vehicle emission standards, and stipulation of targeted testing procedures and testing instruments.
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Affiliation(s)
- Lizhong Xu
- College of Environmental and Resource Sciences, Fujian Key Laboratory of Pollution Control & Resource Reuse, Fujian Normal University, Fuzhou 350007, China; Digital Fujian Internet-of-things Laboratory of Environmental Monitoring, Fuzhou 350007, China
| | - Yumeng Bao
- College of Environmental and Resource Sciences, Fujian Key Laboratory of Pollution Control & Resource Reuse, Fujian Normal University, Fuzhou 350007, China
| | - Hanyang Man
- College of Environmental and Resource Sciences, Fujian Key Laboratory of Pollution Control & Resource Reuse, Fujian Normal University, Fuzhou 350007, China; Digital Fujian Internet-of-things Laboratory of Environmental Monitoring, Fuzhou 350007, China.
| | - Zhining Zhang
- State Key Joint Laboratory of ESPC, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, School of Environment, Tsinghua University, Beijing 100084, China
| | - Jiawei Chen
- College of Environmental and Resource Sciences, Fujian Key Laboratory of Pollution Control & Resource Reuse, Fujian Normal University, Fuzhou 350007, China
| | - Xiaohan Shao
- College of Environmental and Resource Sciences, Fujian Key Laboratory of Pollution Control & Resource Reuse, Fujian Normal University, Fuzhou 350007, China
| | - Bo Zhu
- College of Environmental and Resource Sciences, Fujian Key Laboratory of Pollution Control & Resource Reuse, Fujian Normal University, Fuzhou 350007, China; Digital Fujian Internet-of-things Laboratory of Environmental Monitoring, Fuzhou 350007, China
| | - Huan Liu
- State Key Joint Laboratory of ESPC, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, School of Environment, Tsinghua University, Beijing 100084, China
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Li Z, Xiao H, Walters WW, Hastings MG, Min J, Song L, Lu W, Wu L, Yan W, Liu S, Fang Y. Nitrogen isotopic characteristics of aerosol ammonium in a Chinese megacity indicate the reduction from vehicle emissions during the lockdown period. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 922:171265. [PMID: 38417516 DOI: 10.1016/j.scitotenv.2024.171265] [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: 12/20/2023] [Revised: 02/01/2024] [Accepted: 02/23/2024] [Indexed: 03/01/2024]
Abstract
The role of agricultural versus vehicle emissions in urban atmospheric ammonia (NH3) remains unclear. The lockdown due to the outbreak of COVID-19 provided an opportunity to assess the role of source emissions on urban NH3. Concentrations and δ15N of aerosol ammonium (NH4+) were measured before (autumn in 2017) and during the lockdown (summer, autumn, and winter in 2020), and source contributions were quantified using SIAR. Despite the insignificant decrease in NH4+ concentrations, significantly lower δ15N-NH4+ was found in 2020 (0.6 ± 1.0‰ in PM2.5 and 1.4 ± 2.1‰ in PM10) than in 2017 (15.2 ± 6.7‰ in PM2.5), which indicates the NH3 from vehicle emissions has decreased by∼50% during the lockdown while other source emissions are less affected. Moreover, a reversed seasonal pattern of δ15N-NH4+ during the lockdown in Changsha has been revealed compared to previous urban studies, which can be explained by the dominant effect of non-fossil fuel emissions due to the reductions of vehicle emissions during the lockdown period. Our results highlight the effects of lockdown on aerosol δ15N-NH4+ and the importance of vehicle emissions to urban atmospheric NH3, providing conclusive evidence that reducing vehicle NH3 emissions could be an effective strategy to reduce PM2.5 in Chinese megacities.
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Affiliation(s)
- Zhengjie Li
- National Engineering Laboratory for Applied Technology of Forestry & Ecology in Southern China, College of Biological Science and Technology, Central South University of Forestry and Technology, Changsha, Hunan 410004, China
| | - Hongwei Xiao
- School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Wendell W Walters
- Department of Chemistry and Biochemistry, University of South Carolina, Columbia, SC 29208, USA
| | - Meredith G Hastings
- Institute at Brown for Environment and Society, Department of Earth, Environmental and Planetary Sciences, Brown University, Providence, RI 02912, USA
| | - Juan Min
- National Engineering Laboratory for Applied Technology of Forestry & Ecology in Southern China, College of Biological Science and Technology, Central South University of Forestry and Technology, Changsha, Hunan 410004, China
| | - Linlin Song
- CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China; Key Laboratory of Stable Isotope Techniques and Applications, Liaoning Province 110016, China
| | - Weizhi Lu
- National Engineering Laboratory for Applied Technology of Forestry & Ecology in Southern China, College of Biological Science and Technology, Central South University of Forestry and Technology, Changsha, Hunan 410004, China
| | - Libin Wu
- Institute of Surface-Earth System Science, School of Earth System Science, Tianjin University, Tianjin 300072, China
| | - Wende Yan
- National Engineering Laboratory for Applied Technology of Forestry & Ecology in Southern China, College of Biological Science and Technology, Central South University of Forestry and Technology, Changsha, Hunan 410004, China
| | - Shuguang Liu
- National Engineering Laboratory for Applied Technology of Forestry & Ecology in Southern China, College of Biological Science and Technology, Central South University of Forestry and Technology, Changsha, Hunan 410004, China.
| | - Yunting Fang
- CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China; Key Laboratory of Stable Isotope Techniques and Applications, Liaoning Province 110016, China; Qingyuan Forest CERN, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China.
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Zhu C, Li R, Qiu M, Zhu C, Gai Y, Li L, Yang N, Sun L, Wang C, Wang B, Yan G, Xu C. High spatiotemporal resolution ammonia emission inventory from typical industrial and agricultural province of China from 2000 to 2020. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 918:170732. [PMID: 38340857 DOI: 10.1016/j.scitotenv.2024.170732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Revised: 02/01/2024] [Accepted: 02/03/2024] [Indexed: 02/12/2024]
Abstract
As a typical industrial and agricultural province, Shandong is one of China's most seriously air-polluted regions. One comprehensive ammonia emission inventory with a high spatial resolution (1 km × 1 km) for 136 county-level administrative divisions in Shandong from 2000 to 2020 is developed based on county-level activity data with the corrected and updated emission factors of seventy-seven subcategories. Annual ammonia emissions decrease from 1003.3 Gg in 2000 to 795.9 Gg in 2020, with an annual decrease rate of 1.2 %. Therein, the ammonia emissions associated with livestock and farmland ecosystems in 2020 account for 50.8 % and 32.9 % of the provincial total ammonia emission, respectively. Laying hen and wheat are the livestock and crop with the highest ammonia emissions, accounting for 23.3 % and 36.3 % of ammonia emissions from livestock and the application of synthetic fertilizers, respectively. Furthermore, waste treatment, humans and vehicles are the top three ammonia emission sources in urban areas, accounting for 5.0 %, 4.7 % and 1.3 % of total ammonia emissions, respectively. The spatial distribution of grids with high ammonia emissions is consistent with the distribution of intensive farms. Significant emission intensity areas mainly concentrate in western Shandong (e.g., Caoxian of Heze, Qihe of Dezhou, Yanggu of Liaocheng, Liangshan of Jining) due to the large area of arable land and the high levels of agricultural activity. Overall, prominent seasonal variability characteristics of ammonia emission are observed. Ammonia emissions tend to be high in summer and low in winter, and the August to January-emission ratio is 5.6. The high temperature and fertilization for maize are primarily responsible for Shandong's increase in ammonia emissions in summer. Finally, the validity of the estimates is further evaluated using uncertainty analysis and comparison with previous studies. This study can provide information to determine preferentially effective PM2.5 control strategies.
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Affiliation(s)
- Chuanyong Zhu
- College of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China.
| | - Renqiang Li
- College of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
| | - Mengyi Qiu
- State Grid of China Technology Collage, State Grid, Jinan 250002, China
| | - Changtong Zhu
- College of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
| | - Yichao Gai
- College of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
| | - Ling Li
- Ecology Institute of Shandong Academy of Science, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
| | - Na Yang
- College of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
| | - Lei Sun
- College of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
| | - Chen Wang
- College of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
| | - Baolin Wang
- College of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
| | - Guihuan Yan
- Ecology Institute of Shandong Academy of Science, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
| | - Chongqing Xu
- Ecology Institute of Shandong Academy of Science, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
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