1
|
Fu X, Chen D, Wang X, Li Y, Lang J, Zhou Y, Guo X. The impacts of ship emissions on ozone in eastern China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 903:166252. [PMID: 37574059 DOI: 10.1016/j.scitotenv.2023.166252] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 08/10/2023] [Accepted: 08/10/2023] [Indexed: 08/15/2023]
Abstract
Tropospheric ozone (O3), which is one of the main pollutants impeding air quality compliance, has received considerable attention in China. As maritime transportation continues to expand, the effect of ship emissions on air quality is becoming increasingly important. In this study, the Weather Research and Forecast model (WRF), the Community Multiscale Air Quality model (CMAQ), and the integrated process rate (IPR) module provided in the CMAQ are applied to evaluate the impacts of ship emissions on O3 concentration at a national scale in China, including the spatiotemporal characteristics and influencing pathways. Ship emissions can increase or decrease O3 concentrations, with varying effects in different seasons and regions. In the winter, spring, and fall, ship emissions were predicted to decrease O3 concentrations in most areas, whereas in the summer, they increase the O3 concentration, even in regions far away from the coastline, thus adversely affecting the Yangtze River Delta (YRD) and Pearl River Delta (YRD). Additionally, owing to differences in the emissions of volatile organic compounds and nitrogen oxides, the northern and southern regions of the YRD respond differently to ship emissions. Additionally, the influence of ship emissions on the diurnal variation of O3 in the summer was investigated, where significant differences were indicated between cities. The IPR was used to investigate the individual processes contributing to changes in the O3 concentration caused by ship emissions. The transport process appears to be the primary contributor to O3 production, whereas chemistry and dry deposition played key roles in O3 loss. This study provides an in-depth insight into the impacts of ship emissions on O3 in China, which can facilitate the formulation of corresponding environmental policies.
Collapse
Affiliation(s)
- Xinyi Fu
- Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing 100124, China
| | - Dongsheng Chen
- Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing 100124, China.
| | - Xiaotong Wang
- Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing 100124, China
| | - Yue Li
- Transport Planning and Research Institute, Ministry of Transport, Beijing 100028, China
| | - Jianlei Lang
- Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing 100124, China
| | - Ying Zhou
- Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing 100124, China
| | - Xiurui Guo
- Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing 100124, China
| |
Collapse
|
2
|
Huang H, Zhou C, Huang L, Xiao C, Wen Y, Li J, Lu Z. Inland ship emission inventory and its impact on air quality over the middle Yangtze River, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 843:156770. [PMID: 35728651 DOI: 10.1016/j.scitotenv.2022.156770] [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: 04/07/2022] [Revised: 06/13/2022] [Accepted: 06/14/2022] [Indexed: 06/15/2023]
Abstract
Shipping emissions have been considered a significant source of air pollution in the cities along the Yangtze River, with severe impacts on the climate and human health. This study created a complete annual ship emission inventory for the middle reaches of the Yangtze River and assessed its impact on air quality on a regional scale. To estimate the complete emissions, 9 main engine power regression models for different ship types were created to handle those vessels with absent main power data, and a high spatial-temporal resolution annual emission inventory was developed with the activity-based method combined with Automatic Identification System (AIS) data of the full year of 2018. The total emissions of CO2, CO, SO2, NOX, PM2.5, PM10 and HC in middle reaches of the Yangtze River were 5.67 × 105, 1.02 × 103, 5.41 × 102, 1.06 × 104, 2.43 × 102, 2.45 × 102 and 3.52 × 102 tons respectively. Then, the Weather Research and Forecasting with Chemistry (WRF-Chem) model was used to study the dispersion of the ship pollutants in the atmosphere and quantize the impact on the urban area. This research will provide services for the maritime authorities to develop green shipping and emission supervision.
Collapse
Affiliation(s)
- Hongxun Huang
- School of Navigation, Wuhan University of Technology, Wuhan, China; Hubei Key Laboratory of Inland Shipping Technology, Wuhan, China
| | - Chunhui Zhou
- School of Navigation, Wuhan University of Technology, Wuhan, China; Hubei Key Laboratory of Inland Shipping Technology, Wuhan, China; Laboratory of Transport Pollution Control and Monitoring Technology, Beijing, China.
| | - Liang Huang
- Intelligent Transportation System Research Center, Wuhan University of Technology, Wuhan, China; National Engineering Research Center for Water Transport Safety, Wuhan University of Technology, Wuhan, China
| | - Changshi Xiao
- School of Navigation, Wuhan University of Technology, Wuhan, China; Hubei Key Laboratory of Inland Shipping Technology, Wuhan, China; National Engineering Research Center for Water Transport Safety, Wuhan University of Technology, Wuhan, China
| | - Yuanqiao Wen
- Intelligent Transportation System Research Center, Wuhan University of Technology, Wuhan, China; National Engineering Research Center for Water Transport Safety, Wuhan University of Technology, Wuhan, China
| | - Jing Li
- School of Navigation, Wuhan University of Technology, Wuhan, China; Hubei Key Laboratory of Inland Shipping Technology, Wuhan, China
| | - Zhigang Lu
- Zhejiang Scientific Research Institute of Transport, Hangzhou, China
| |
Collapse
|
3
|
Combustion Performance and Emission Characteristics of Marine Engine Burning with Different Biodiesel. ENERGIES 2022. [DOI: 10.3390/en15145177] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Ship emissions are one of the main sources of air pollution in port cities. The prosperous maritime trade has brought great harm to the air quality of port cities while promoting the development of the world economy. During the berthing process, ship auxiliary machines emit a large amount of air pollutants, which have a great impact on air quality and public health. Alternative marine fuels are being studied and used frequently to reduce ship emissions. This research was carried out to investigate the gaseous and particles emission characteristics of a marine diesel engine during the application of experimental biodiesel fuels. To study the influence of mixed fuels on engine performance, measurements were made at different engine loads and speeds. Different diesel fuels were tested using various ratios between biodiesel and BD0 (ultra-low sulfur diesel) of 0%, 10%, 30%, 50%, 70%, 90%, and 100%. The results indicated the use of biodiesel has little influence on the combustion performance but has a certain impact on exhaust emissions. The octane number and laminar flame speed of biodiesel are higher than those of BD0, so the combustion time of the test diesel engine is shortened under the mixed mode of biodiesel. In addition, a high ratio of biodiesel leads to a decrease of the instantaneous peak heat release rate, causing the crank angle to advance. As the biodiesel blending ratio increased, most of the gaseous pollutants decreased, especially for CO, but it led to an increase of particle numbers. The particle size distribution exhibits a unimodal distribution under various conditions, with the peak value appearing at 30–75 nm. The use of biodiesel has no effect on this phenomenon. The peak positions strongly depend on fuel types and engine conditions. The particulate matter (PM) emitted from the test engine included large amounts of organic carbon (OC), which accounted for between 30% and 40% of PM. Whereas the elemental carbon (EC) accounted for between 10% and 20%, the water-soluble ions components accounted for 6–15%. Elemental components, which accounted for 3–8% of PM emissions, mainly consisted of Si, Fe, Sn, Ba, Al, Zn, V, and Ni. Generally, biodiesel could be a reliable alternative fuel to reduce ship auxiliary engine emissions at berth and improve port air quality.
Collapse
|
4
|
Impact of Sea Breeze on the Transport of Ship Emissions: A Comprehensive Study in the Bohai Rim Region, China. ATMOSPHERE 2022. [DOI: 10.3390/atmos13071094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Air pollutants from ship exhaust have a negative impact on air quality in coastal areas, which can be greatly exacerbated by sea breeze circulation. However, our understanding of this issue is still limited, especially in coastal areas with a complex topography and winding coastlines, such as the Bohai Rim region in China. In order to fill this knowledge gap, the Weather Research and Forecast model coupled with the chemistry (WRF/Chem) modeling system was employed to investigate the influence of sea breeze circulation on the transport of PM2.5 emitted by ships from April to September in 2014. The major findings are as follows: (1) The concentration of PM2.5 due to ship emissions was 2.94 μg/m3 on days with a sea breeze and 2.4 times higher than on days without a sea breeze in coastal cities in the region. (2) The difference in the contribution of ship emissions during days with a sea breeze and days without a sea breeze decreases with increasing distance from the coastline but remains non-negligible up to 50 km inland. (3) The shape of the coastline, the topographic height of the land area, and the latitude have a significant impact on sea breeze circulation and thus on the transport of ship emissions. (4) The differences in the contribution of ship emissions under days with a sea breeze versus days without a sea breeze were more evident than those under onshore versus alongshore and offshore winds, indicating that sea breeze circulation can cause cyclic accumulation of pollutants and thus reinforce the impact of ship emissions on coastal air quality more than by onshore winds. It should be emphasized that during the switching from sea breeze to a non-sea breeze, the pollutants that have been transported to the land area by sea breeze have not yet been carried back to sea, resulting in the ship contribution value still not significantly reduced even if the wind is a non-sea breeze at that moment. In addition, other factors e.g., emissions, precipitation, and chemistry can also play an important role in the observed trends in this study.
Collapse
|
5
|
Ye Z, Li J, Pan Y, Wang Z, Guo X, Cheng L, Tang X, Zhu J, Kong L, Song Y, Xing J, Sun Y, Pan X. Synergistic effect of reductions in multiple gaseous precursors on secondary inorganic aerosols in winter under a meteorology-based redistributed daily NH 3 emission inventory within the Beijing-Tianjin-Hebei region, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 821:153383. [PMID: 35085635 DOI: 10.1016/j.scitotenv.2022.153383] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Revised: 12/30/2021] [Accepted: 01/20/2022] [Indexed: 06/14/2023]
Abstract
Secondary inorganic aerosols (SIA) account for 20-60% of the total fine particulates in the Beijing-Tianjin-Hebei (BTH) region of China, indicating an urgent need to clarify the relationship among such compounds. The purpose of this study was to quantify the relationship between emissions of NH3, NOx, SO2, VOCs and SIA concentrations during a severe winter haze episode using an air quality model and a meteorology-based redistributed NH3 emission inventory within the BTH region. The results showed that the model performance regarding the NH3 simulations in January by the four emission inventories improved after the redistribution of daily NH3 emissions, with an increase of 0.02-0.13 in R, a 9-56% decrease in NMB, and a 7-51% decrease in NME. The updated simulations reproduced the daily observations of SIA, SO2, and NO2 well. A total of 125 sets of sensitivity simulations showed that a synergistic reduction in NH3 and VOCs was more efficient in terms of SIA control than simply reducing SO2 or NOx in the BTH region. If only NOx emissions were reduced, the SIA concentration would first increase and then decrease, and it could decline by another 0.86-8.03% in parallel with an equal NH3 emission cut. SIA could be reduced by approximately 22.68% with the most stringent inorganic precursors' control. Moreover, VOCs emission reductions could lead to a decrease in SIA, and the impact of VOCs on SIA was similar to that of NH3. The collaborative control of both inorganic precursors and VOCs was more effective than single-factor control measures for decreasing SIA, and the decline rate was approximately 29.26% under minimum emission conditions. This improved effectiveness was obtained because VOCs mitigation effectively decreases the ozone concentration, which in turn influences SIA formation. Finally, on the premise of a 60% SO2 cut, the reduction scheme NH3:VOCs:NOx = 4:4:1 was suggested for SIA control.
Collapse
Affiliation(s)
- Zhilan Ye
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Jie Li
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China.
| | - Yuepeng Pan
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Zifa Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Xiurui Guo
- College of Environmental & Energy Engineering, Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing 100124, China
| | - Long Cheng
- College of Environmental & Energy Engineering, Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing 100124, China
| | - Xiao Tang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Jiang Zhu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Lei Kong
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Yu Song
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, Department of Environmental Science, Peking University, Beijing 100871, China
| | - Jia Xing
- School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, China
| | - Yele Sun
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Xiaole Pan
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| |
Collapse
|
6
|
Lin YC, Yu M, Xie F, Zhang Y. Anthropogenic Emission Sources of Sulfate Aerosols in Hangzhou, East China: Insights from Isotope Techniques with Consideration of Fractionation Effects between Gas-to-Particle Transformations. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:3905-3914. [PMID: 35294169 DOI: 10.1021/acs.est.1c05823] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Sulfate (SO42-) is a major species in atmospheric fine particles (PM2.5), inducing haze formation and influencing Earth's climate. In this study, the δ34S values in PM2.5 sulfate (δ34S-SO42-) were measured in Hangzhou, east China, from 2015 September to 2016 October. The result showed that the δ34S-SO42- values varied from 1.6 to 6.4‰ with the higher values in the winter. The estimated fractionation factor (α34Sg→p) from SO2 to SO42- averaged at 3.9 ± 1.6‰. The higher α34Sg→p values in the winter were mainly attributed to the decrease of ambient temperature. We further compared the quantified source apportionments of sulfate by isotope techniques with and without the consideration of fractionation factors. The result revealed that the partitioned emission sources to sulfate with the consideration of the fractionation effects were more logical, highlighting that fractionation effects should be considered in partitioning emission sources to sulfate using sulfur isotope techniques. With considering the fractionation effects, coal burning was the dominant source to sulfate (85.5%), followed by traffic emissions (12.8%) and oil combustion (1.7%). However, the coal combustion for residential heating contributed only 0.9% to sulfate on an annual basis in this megacity.
Collapse
Affiliation(s)
- Yu-Chi Lin
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China
- Key Laboratory Meteorological Disaster; Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing 210044, China
- Jiangsu Provincial Key Laboratory of Agricultural Meteorology, School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Mingyuan Yu
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China
- Key Laboratory Meteorological Disaster; Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing 210044, China
- Jiangsu Provincial Key Laboratory of Agricultural Meteorology, School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Feng Xie
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China
- Key Laboratory Meteorological Disaster; Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing 210044, China
- Jiangsu Provincial Key Laboratory of Agricultural Meteorology, School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Yanlin Zhang
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China
- Key Laboratory Meteorological Disaster; Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing 210044, China
- Jiangsu Provincial Key Laboratory of Agricultural Meteorology, School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China
| |
Collapse
|
7
|
The Temporal and Spatial Changes of Ship-Contributed PM2.5 Due to the Inter-Annual Meteorological Variation in Yangtze River Delta, China. ATMOSPHERE 2021. [DOI: 10.3390/atmos12060722] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Ship-exhausted air pollutants could cause negative impacts on air quality, climate change, and human health. Increasing attention has been paid to investigate the impact of ship emissions on air quality. However, the conclusions are often based on a specific year, the extent to which the inter-annual variation in meteorological conditions affects the contribution is not yet fully addressed. Therefore, in this study, the Weather Research and Forecast model and the Community Multiscale Air Quality model(WRF/CMAQ) were employed to investigate the inter-annual variations in ship-contributed PM2.5 from 2010 to 2019. The Yangtze River Delta (YRD) region in China was selected as the target study area. To highlight the impact of inter-annual meteorological variations, the emission inventory and model configurations were kept the same for the 10-year simulation. We found that: (1) inter-annual meteorological variation had an evident impact on the ship-contributed PM2.5 in most coastal cities around YRD. Taking Shanghai as an example, the contribution varied between 3.05 and 5.74 µg/m3, with the fluctuation rate of ~65%; (2) the inter-annual changes in ship’s contribution showed a trend of almost simultaneous increase and decrease for most cities, which indicates that the impact of inter-annual meteorological variation was more regional than local; (3) the inter-annual changes in the northern part of YRD were significantly higher than those in the south; (4) the most significant inter-annual changes were found in summer, followed by spring, fall and winter.
Collapse
|
8
|
|
9
|
Jiang J, Aksoyoglu S, Ciarelli G, Baltensperger U, Prévôt ASH. Changes in ozone and PM 2.5 in Europe during the period of 1990-2030: Role of reductions in land and ship emissions. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 741:140467. [PMID: 32886963 DOI: 10.1016/j.scitotenv.2020.140467] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Revised: 06/21/2020] [Accepted: 06/22/2020] [Indexed: 06/11/2023]
Abstract
Air pollution is among the top threats to human health and ecosystems despite the substantial decrease in anthropogenic emissions. Meanwhile, the role of ship emissions on air quality is becoming increasingly important with the growing maritime transport and less strict regulations. In this study, we modeled the air quality in Europe between 1990 and 2030 with ten-year intervals, using the regional air quality model CAMx version 6.50, to investigate the changes in the past (1990-2010) as well as the effects of different land and ship emission scenarios in the future (2020,2030). The modeled mean ozone levels decreased slightly during the first decade but then started increasing again especially in polluted areas. Results from the future scenarios suggest that by 2030 the peak ozone would decrease, leading to a decrease in the days exceeding the maximum daily 8-h average ozone (MDA8) limit values (60 ppb) by 51% in southern Europe relative to 1990. The model results show a decrease of 56% (6.3 μg m-3) in PM2.5 concentrations from 1990 to 2030 under current legislation, mostly due to a large drop in sulfate (representing up to 44% of the total PM2.5 decrease during 1990-2000) while nitrate concentrations were predicted to go down with an increasing rate (10% of total PM2.5 decrease during 1990-2000 while 36% during 2020-2030). The ship emissions if reduced according to the maximum technically feasible reduction (MTFR) scenario were predicted to contribute up to 19% of the decrease in the PM2.5 concentrations over land between 2010 and 2030. Ship emission reductions according to the MTFR scenario would lead to a decrease in the days with MDA8 exceeding EU limits by 24-28% (10-14 days) around the coastal regions. The results obtained in our study show the increasing importance of ship emission reductions, after a relatively large decrease in land emissions was achieved in Europe.
Collapse
Affiliation(s)
- Jianhui Jiang
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, 5232 Villigen PSI, Switzerland.
| | - Sebnem Aksoyoglu
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, 5232 Villigen PSI, Switzerland.
| | - Giancarlo Ciarelli
- Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA; Now at: Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Finland
| | - Urs Baltensperger
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, 5232 Villigen PSI, Switzerland
| | - André S H Prévôt
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, 5232 Villigen PSI, Switzerland
| |
Collapse
|
10
|
Estimation of the Non-Greenhouse Gas Emissions Inventory from Ships in the Port of Incheon. SUSTAINABILITY 2020. [DOI: 10.3390/su12198231] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Nowadays, maritime air pollution is regarded as a severe threat to coastal communities’ health. Therefore, many policies to reduce air pollution have been established worldwide. Moreover, there has been a shift in policy and research attention from greenhouse gases, especially CO2, to other air pollutants. To address the current local environmental challenges, this research analyzes the non-greenhouse gas emissions inventory (CO, NOx, SOx, PM, VOC, and NH3) from ships in the second biggest port in Korea, the Port of Incheon (POI). A bottom-up activity-based methodology with real-time vessel activity data produced by the Vessel Traffic Service (VTS) is applied to obtain reliable estimations. NOx and SOx dominated the amount of emission emitted from ships. Tankers, general cargo ships, cruise ships, and container ships were identified as the highest sources of pollution. Based on the above results, this study discusses the need for long-term policies, such as the designation of a local emission control area (ECA) and the establishment of an emission management platform to reduce ship-source emissions. Furthermore, this study elucidates that significant emissions come from the docking process, ranging from 33.9% to 42.0% depending on the type of pollutant when only the auxiliary engines were being operated. Therefore, short-term solutions like applying exhausted gas cleaning systems, using on-shore power supplies, reducing docking time, or using greener alternative fuels (e.g., liquefied natural gas or biofuels) should be applied and motivated at the POI. These timely results could be useful for air quality management decision-making processes for local port operators and public agencies.
Collapse
|
11
|
Effect of Seasonal Flow Field on Inland Ship Emission Assessment: A Case Study of Ferry. SUSTAINABILITY 2020. [DOI: 10.3390/su12187484] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The purpose of this paper is to evaluate the effect of the seasonal flow field on inland ship emissions and to improve calculation accuracy. Firstly, the flow field model is built through numerical simulation to correct the sailing speed of the ship from the Automatic Identification System (AIS) information in real-time. Then, an optimal emission estimation model for inland ships considering flow field factors is proposed. Finally, the effectiveness of the optimization model is demonstrated by a case study, and the influence of the seasonal flow field on emission calculation is analyzed. It indicates that the calculation results of the model considering the influence of the flow field are more accurate. Without considering the flow field, the results of emission calculations are often underestimated, especially in summer, which shows the importance of incorporating the flow field factors into the calculation of inland ship emissions.
Collapse
|
12
|
Zhao J, Zhang Y, Patton AP, Ma W, Kan H, Wu L, Fung F, Wang S, Ding D, Walker K. Projection of ship emissions and their impact on air quality in 2030 in Yangtze River delta, China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2020; 263:114643. [PMID: 33618465 DOI: 10.1016/j.envpol.2020.114643] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2019] [Revised: 04/17/2020] [Accepted: 04/19/2020] [Indexed: 06/12/2023]
Abstract
China has been in the implementation phase of Domestic Ship Emission Control Areas (DECAs) regulation to reduce emissions of air pollutants from ships near populated areas since 2016. The Yangtze River Delta (YRD) is one of the busiest port clusters in the world, accounting for 11% of global seaborne cargo throughput, so future improvements in shipping emission controls may still be important in this region. To assess the impact of future ship emissions on air quality of coastal areas, this study evaluates emissions reductions and air quality in 2030 for three scenarios (business as usual, stricter regulations, and aspirational policies) representing increasing levels of control compared with a base year of 2015. We projected ship emissions in the region using a bottom-up approach developed in this study and based on the historical ship automatic identification system (AIS) activity data. We then predicted air quality across the YRD region in 2030 using the Community Multiscale Air Quality (CMAQ) model. The annual average contributions of ship emissions to ambient PM2.5 would decrease by 70.9%, 80.4%, and 86.2% relative to 2015 under the three scenarios, with the largest reductions of more than 4.1 μg/m3 near Shanghai Port under the aspirational scenario. Reductions in ship emissions generally led to lower levels of PM2.5, particularly in most of the coastal cities in the YRD. Compared with a business-as-usual approach the aspirational scenario reduced SO2, NOx and PM2.5 concentrations from shipping by 71.8%, 61.1% and 52.5%, respectively. It was also more effective than the stricter regulation scenario, suggesting that the requirement to use 0.1% sulfur fuel within a 100Nm DECA would have additional benefits to ambient PM2.5 concentrations beyond 12Nm DECA area. This study provides evidence to inform deliberations on the potential air quality benefits of future control policies for ship emissions in China.
Collapse
Affiliation(s)
- Junri Zhao
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai, 200438, China; Big Data Institute for Carbon Emission and Environmental Pollution, Fudan University, Shanghai, 200433, China
| | - Yan Zhang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai, 200438, China; Shanghai Institute of Eco-Chongming (SIEC), Shanghai, 200062, China; Institute of Atmospheric Science, Fudan University, Shanghai, 200438, China.
| | - Allison P Patton
- Health Effects Institute, 75 Federal Street, Suite 1400, Boston, MA, 02110-1817, USA
| | - Weichun Ma
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai, 200438, China; Shanghai Institute of Eco-Chongming (SIEC), Shanghai, 200062, China; Big Data Institute for Carbon Emission and Environmental Pollution, Fudan University, Shanghai, 200433, China
| | - Haidong Kan
- Public Health School, Fudan University, Shanghai, 200032, China
| | - Libo Wu
- Big Data Institute for Carbon Emission and Environmental Pollution, Fudan University, Shanghai, 200433, China
| | - Freda Fung
- Natural Resources Defense Council, China
| | - Shuxiao Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Dian Ding
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Katherine Walker
- Health Effects Institute, 75 Federal Street, Suite 1400, Boston, MA, 02110-1817, USA
| |
Collapse
|
13
|
Mao J, Zhang Y, Yu F, Chen J, Sun J, Wang S, Zou Z, Zhou J, Yu Q, Ma W, Chen L. Simulating the impacts of ship emissions on coastal air quality: Importance of a high-resolution emission inventory relative to cruise- and land-based observations. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 728:138454. [PMID: 32570333 DOI: 10.1016/j.scitotenv.2020.138454] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/25/2019] [Revised: 04/02/2020] [Accepted: 04/03/2020] [Indexed: 06/11/2023]
Abstract
This work studied the impacts of ship emissions at a high temporal resolution on the real-time concentrations of PM2.5, NO2, and SO2 in urban harbors and coastal sea areas, taking the Yangtze River Delta (YRD) as an example. The WRF-Chem model with 3 nested grids and ship emissions derived from an automatic identification system (AIS) were combined to simulate the air quality. The AIS data showed significant temporal fluctuations in ship emissions, with hourly mean fluxes of approximately 1082.41 ± 444.41 and 593.55 ± 404.95 g/h/km2 near ports and in the channel waters of the YRD, respectively. The monthly mean contributions of shipping emissions reached 80.72% (2.15 ppbv) and 81.79% (8.79 ppbv) to ambient SO2 and NO2 in Ningbo Port, and 10.61% (6.96 μg/m3) to PM2.5 in Shanghai Port, respectively, regions with dense ship traffic. The relative differences in the PM2.5, SO2, and NO2 concentrations modeled using monthly and hourly ship emissions accounted for -10-15%, -10-30%, and - 5-30%, respectively. Compared with cruise- and land-based measurements, the simulations using hourly emissions were in much better agreement with the observations than those using monthly emissions and appropriately captured some air pollutant concentration peaks. Simulations during shipping-related periods with hourly ship emissions improved the normalized mean bias (NMBs) from -43.03%, 301.49%, and 223.02% to -27.28%, 90.45%, and 167.52%, respectively, for PM2.5, SO2, and NO2, highlighting the importance of using ship emissions with a fine temporal resolution. Our study showed that ignoring hourly fluctuations in ship emissions during air quality modeling leads to considerable uncertainties, especially in coastal urban areas and harbors with high ship activities. These results imply that data with a high temporal resolution, such as hourly ship emissions, are necessary to understand the realistic impacts of shipping traffic and to implement more precise control policies to improve coastal air quality.
Collapse
Affiliation(s)
- Jingbo Mao
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
| | - Yan Zhang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China; Shanghai Institute of Eco-Chongming (SIEC), Shanghai 200062, China; Institute of Atmospheric Science, Fudan University, Shanghai 200438, China.
| | - Fangqun Yu
- Atmospheric Sciences Research Center, State University of New York, 251 Fuller Road, Albany, NY 12203, USA
| | - Jianmin Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China; Shanghai Institute of Eco-Chongming (SIEC), Shanghai 200062, China
| | - Jianfeng Sun
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
| | - Shanshan Wang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China; Shanghai Institute of Eco-Chongming (SIEC), Shanghai 200062, China
| | - Zhong Zou
- Pudong New Area Environmental Monitoring Station, Shanghai 200135, China
| | - Jun Zhou
- Ningbo Environmental Monitoring Center, Ningbo 315012, China
| | - Qi Yu
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
| | - Weichun Ma
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
| | - Limin Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China.
| |
Collapse
|
14
|
Guo X, Wu H, Chen D, Ye Z, Shen Y, Liu J, Cheng S. Estimation and prediction of pollutant emissions from agricultural and construction diesel machinery in the Beijing-Tianjin-Hebei (BTH) region, China ☆. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2020; 260:113973. [PMID: 31991351 DOI: 10.1016/j.envpol.2020.113973] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Revised: 01/10/2020] [Accepted: 01/11/2020] [Indexed: 05/19/2023]
Abstract
Both agricultural and construction machinery are important non-road sources of atmospheric pollution, with total hydrocarbons (THC), nitrogen oxides (NOx) and particulate matter (PM) emissions accounting for more than 60% of the total emissions from all non-road mobile sources in China. However, there exist relatively few efforts to establish the emission inventory for these machineries. This study attempted to estimate and predict air pollutant emissions from agricultural and construction diesel machinery, using the Beijing-Tianjin-Hebei (BTH) region as the case study area. The results show that total emissions of PM10, PM2.5, THC, NOX, CO and SO2 in 2015 were 41.10, 38.80, 86.14, 520.41, 379.01 and 17.32 Kt respectively. The contribution of agricultural machinery was slightly higher than that of construction machinery, accounting for 60-71% of the total. Moreover, emissions of various pollutants (except SO2) from agricultural machinery were mainly distributed in central Hebei (Cangzhou, Shijiazhuang and Baoding), while emissions from construction machinery were mainly distributed in Beijing and Tianjin. The prediction suggest that the total emissions of agricultural and construction diesel machinery in the BTH region would increase by 6% in 2020 and 9% in 2025. Moreover, pollutant emissions from construction machinery would contribute from 29% to 40% in 2015 to 34%-61% in 2025. These results could provide important information for making effective mitigation measures of non-road mobile sources.
Collapse
Affiliation(s)
- Xiurui Guo
- College of Environmental & Energy Engineering, Key Laboratory of Regional Atmospheric Compound Pollution Prevention in Beijing, Beijing University of Technology, Beijing, 100124, China.
| | - Hongkan Wu
- College of Environmental & Energy Engineering, Key Laboratory of Regional Atmospheric Compound Pollution Prevention in Beijing, Beijing University of Technology, Beijing, 100124, China
| | - Dongsheng Chen
- College of Environmental & Energy Engineering, Key Laboratory of Regional Atmospheric Compound Pollution Prevention in Beijing, Beijing University of Technology, Beijing, 100124, China.
| | - Zhilan Ye
- College of Environmental & Energy Engineering, Key Laboratory of Regional Atmospheric Compound Pollution Prevention in Beijing, Beijing University of Technology, Beijing, 100124, China
| | - Yaqian Shen
- College of Environmental & Energy Engineering, Key Laboratory of Regional Atmospheric Compound Pollution Prevention in Beijing, Beijing University of Technology, Beijing, 100124, China
| | - Junfang Liu
- College of Environmental & Energy Engineering, Key Laboratory of Regional Atmospheric Compound Pollution Prevention in Beijing, Beijing University of Technology, Beijing, 100124, China
| | - Shuiyuan Cheng
- College of Environmental & Energy Engineering, Key Laboratory of Regional Atmospheric Compound Pollution Prevention in Beijing, Beijing University of Technology, Beijing, 100124, China
| |
Collapse
|
15
|
Liu J, Shen J, Cheng Z, Wang P, Ying Q, Zhao Q, Zhang Y, Zhao Y, Fu Q. Source apportionment and regional transport of anthropogenic secondary organic aerosol during winter pollution periods in the Yangtze River Delta, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 710:135620. [PMID: 31785922 DOI: 10.1016/j.scitotenv.2019.135620] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2019] [Revised: 11/17/2019] [Accepted: 11/17/2019] [Indexed: 06/10/2023]
Abstract
Since the concentrations of primary particles and secondary inorganic aerosol components have been reduced significantly due to stringent emission controls, quantifying the source contributions and regional transport of secondary organic aerosol (SOA) is critical to further improve air quality in eastern China. In this study, the Community Multiscale Air Quality (CMAQ) model coupled with the updated SAPRC-11 photochemical mechanism and a revised SOA module was applied to investigate the emission sector and regional contributions to SOA in winter 2015 (January 5-26, 2015) and 2016 (December 20, 2015-January 20, 2016) in the Yangtze River Delta (YRD). The model is generally capable of reproducing the observed SOA concentrations at the Qingpu Supersite in Shanghai. The observed and predicted SOA concentrations are 6.4 μg/m3 and 6.9 μg/m3 in winter 2015, and 5.7 μg/m3 and 9.6 μg/m3 in winter 2016. The mean fraction bias (MFB) of the hourly SOA predictions is 0.22 and 0.32, respectively. High SOA concentrations in the wintertime of YRD are mainly due to aromatic compounds and dicarbonyls (glyoxal and methylglyoxal), which, on average, account for 43% and 53% of total SOA, respectively. The average contributions of industrial, residential, and transportation sectors in the YRD region during the entire simulation periods are 61%, 22%, and 17%, respectively. At the Qingpu Supersite in Shanghai, the industrial sector contributes to as much as 65% of total SOA in the heavy pollution episode of 2016. The contributions from transportation and residential sectors are 16% and 17%, respectively, during the same episode. The industry emissions from the Jiangsu, Zhejiang, and Shanghai are major contributors to the SOA at the Qingpu supersite during the heavy-polluted episodes, accounting for 31%, 19%, and 14% of the total predicted SOA. This study represents the first detailed regional modeling study of source region contributions to SOA in the YRD region and the detailed analyses of SOA in two winters months complement the previous SOA source apportionment studies focusing on seasonal average contributions.
Collapse
Affiliation(s)
- Jie Liu
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Juanyong Shen
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Zhen Cheng
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
| | - Peng Wang
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, 999077, Hong Kong, China.
| | - Qi Ying
- Zachry Department of Civil Engineering, Texas A&M University, College Station, TX 77843, USA
| | - Qianbiao Zhao
- Shanghai Environmental Monitoring Center, Shanghai 200235, China
| | - Yihua Zhang
- Shanghai Environmental Monitoring Center, Shanghai 200235, China
| | - Yue Zhao
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Qingyan Fu
- Shanghai Environmental Monitoring Center, Shanghai 200235, China
| |
Collapse
|
16
|
Chen D, Fu X, Guo X, Lang J, Zhou Y, Li Y, Liu B, Wang W. The impact of ship emissions on nitrogen and sulfur deposition in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 708:134636. [PMID: 31791755 DOI: 10.1016/j.scitotenv.2019.134636] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2019] [Revised: 08/29/2019] [Accepted: 09/23/2019] [Indexed: 06/10/2023]
Abstract
A large amount of NOX and SO2 emitted from ships may elevate atmospheric N and S and eventually aggravate the deposition of N and S. The understanding of N and S deposition due to ship emissions is still limited, especially for China because it has a long coastline, busy shipping routes, and several large ports. To fill this gap, a comprehensive air quality model was employed in this study to quantify the contributions of ship emissions to N and S deposition on a national scale in China. Both the spatial and temporal variations of N and S deposition, as well as the major N and S species from ship traffic, were investigated. The results indicate that ship emissions contributed significantly to the deposition of N and S, especially in coastal and offshore areas, where the largest ship contribution to both N and S deposition could exceed 15 kg·ha-1·yr-1. For N deposition, ship emissions caused an increase in the total N deposition, not only in port areas and along shipping routes but also far inland, with evident seasonal variations. The contribution from dry N deposition was evidently larger than wet N deposition, especially over the coastal areas. S deposition, however, was generally higher along shipping routes but exhibited distinct seasonal variations. The total S deposition was dominated by dry deposition, especially over offshore areas. Ship-caused dry S deposition occurred mainly in offshore areas, while wet S deposition could be found over wider inland regions and inland waterways, although with a markedly smaller magnitude.
Collapse
Affiliation(s)
- Dongsheng Chen
- Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing 100124, China.
| | - Xinyi Fu
- Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing 100124, China
| | - Xiurui Guo
- Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing 100124, China
| | - Jianlei Lang
- Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing 100124, China
| | - Ying Zhou
- Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing 100124, China
| | - Yue Li
- Transport Planning and Research Institute, Ministry of Transport, Beijing 100028, China
| | - Bo Liu
- School of Geography Science, Nantong University, Nantong, China.
| | - Wenlin Wang
- Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing, China
| |
Collapse
|
17
|
Impact of Sea Breeze Circulation on the Transport of Ship Emissions in Tangshan Port, China. ATMOSPHERE 2019. [DOI: 10.3390/atmos10110723] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
A sea breeze is a local circulation that occurs in coastal regions from the poles to the equator. The adverse influence of ship emissions on air quality in coastal areas may be aggravated by the onshore flow of sea breeze circulation. However, our knowledge regarding the evolution of ship-emitted pollutants during a specific sea breeze episode is still limited. To address this knowledge gap, this study investigated the evolution of ship emissions during a sea breeze episode that occurred on 29 June, 2014 in Tangshan port in China by employing the WRF/Chem model. NO2, one of the primary pollutants emitted by ships, was selected as the target pollutant for investigation. The results indicate that the ground level NO2 concentration was considerably affected by sea breeze circulation. Although the onset of the sea breeze was delayed until nearly midday due to offshore synoptic winds, ship-emitted NO2 was transported to more than 100 km inland with the penetration of the sea breeze. Further investigation found that the averaged concentration of ship-contributed NO2 during the episode showed an evident downward trend as the distance from the coastline increased. Vertically, the shallow atmospheric boundary layer (ABL) on the sea limited the vertical dispersion of ship emissions, and the pollutant was transported shoreward by the sea breeze within this shallow ABL. The height of the ABLs is lowered in coastal regions due to the cooling effect of sea breezes which brings the cool marine air to the hot land surface. Ship-contributed NO2 was mostly trapped in the shallow ABL; thereby, its concentration increased.
Collapse
|
18
|
Peng J, Huang Y, Liu T, Jiang L, Xu Z, Xing W, Feng X, De Maeyer P. Atmospheric nitrogen pollution in urban agglomeration and its impact on alpine lake-case study of Tianchi Lake. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 688:312-323. [PMID: 31233913 DOI: 10.1016/j.scitotenv.2019.06.202] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Revised: 05/30/2019] [Accepted: 06/13/2019] [Indexed: 06/09/2023]
Abstract
The atmospheric pollution caused by human activities has been recognized as an important factor affecting the water quality of freshwater bodies. The process of the human factors' impact on high-altitude lakes in inland regions is not clear up to now. In this research, regions around Tianchi Lake were taken as a case study to explore the relation between the urban air pollution and alpine lake water quality. Multi-scale station observed data were analyzed for the urban NO2 pollution by means of relevance analysis and trend analysis, the field measured data were analyzed for the lake total nitrogen (TN) pollution using multiple methods including the water quantity and quality balance, remote sensing retrieval and nutrient load assessment. The sources and occurrence conditions of atmospheric pollution and lake pollution were identified by a multi-method driving factor analysis. As a result, there is sufficient direct and indirect evidence to prove that the serious air pollution in surrounding cities is an important cause of the nitrogen pollution in Tianchi Lake.
Collapse
Affiliation(s)
- Jiabin Peng
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; Key Laboratory of GIS & RS Application Xinjiang Uygur Autonomous Region, Urumqi 830011, China; University of Chinese Academy of Sciences, Beijing 100049, China; Department of Geography, Ghent University, Ghent 9000, Belgium; Sino-Belgian Joint Laboratory of Geo-information, Urumqi 830011, China; Sino-Belgian Joint Laboratory of Geo-information, Ghent 9000, Belgium
| | - Yue Huang
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; Key Laboratory of GIS & RS Application Xinjiang Uygur Autonomous Region, Urumqi 830011, China.
| | - Tie Liu
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; Key Laboratory of GIS & RS Application Xinjiang Uygur Autonomous Region, Urumqi 830011, China; Sino-Belgian Joint Laboratory of Geo-information, Urumqi 830011, China; Sino-Belgian Joint Laboratory of Geo-information, Ghent 9000, Belgium
| | - Liangliang Jiang
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; Key Laboratory of GIS & RS Application Xinjiang Uygur Autonomous Region, Urumqi 830011, China; University of Chinese Academy of Sciences, Beijing 100049, China; Department of Geography, Ghent University, Ghent 9000, Belgium; Sino-Belgian Joint Laboratory of Geo-information, Urumqi 830011, China; Sino-Belgian Joint Laboratory of Geo-information, Ghent 9000, Belgium
| | - Zhu Xu
- Xinjiang Tianchi Management Committee, Fukang 831500, China
| | - Wei Xing
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
| | - Xianwei Feng
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
| | - Philippe De Maeyer
- Department of Geography, Ghent University, Ghent 9000, Belgium; Sino-Belgian Joint Laboratory of Geo-information, Urumqi 830011, China; Sino-Belgian Joint Laboratory of Geo-information, Ghent 9000, Belgium
| |
Collapse
|
19
|
Dong YM, Liao LY, Li L, Yi F, Meng H, He YF, Guo MM. Skin inflammation induced by ambient particulate matter in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 682:364-373. [PMID: 31125750 DOI: 10.1016/j.scitotenv.2019.05.155] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2019] [Revised: 04/29/2019] [Accepted: 05/11/2019] [Indexed: 06/09/2023]
Abstract
Most published studies on particulate matter (PM) concerning PM2.5 and PM10 have focused on PM-induced effects on the respiratory system (particularly lung) and cardiovascular system effects. However, epidemiological and mechanistic studies suggest that PM2.5 and PM10 also affects the skin, which is a key health issue. In this study, we first reviewed the current status of PM2.5 and PM10 in China, including relevant regulations, concentration levels, chemical components, and emission sources. Next, we summarized the association between PM2.5 and PM10 or its representative components, in relation to skin inflammation as well as inflammatory skin diseases, such as atopic dermatitis, acne, eczema, and skin aging. Finally, we determined the mechanism of oxidative stress or programmed cell death induced through PM, which can provide useful information for future research on PM-induced skin inflammation.
Collapse
Affiliation(s)
- Yin-Mao Dong
- Key Laboratory of Cosmetics, China National Light Industry, Beijing Technology and Business University, No. 11/33, Fucheng Road, Haidian District, Beijing 100048, PR China; Beijing Key Laboratory of Plant Resources Research and Development, Beijing Technology and Business University, No. 11/33, Fucheng Road, Haidian District, Beijing 100048, PR China
| | - Lian-Ying Liao
- Key Laboratory of Cosmetics, China National Light Industry, Beijing Technology and Business University, No. 11/33, Fucheng Road, Haidian District, Beijing 100048, PR China; Beijing Key Laboratory of Plant Resources Research and Development, Beijing Technology and Business University, No. 11/33, Fucheng Road, Haidian District, Beijing 100048, PR China
| | - Li Li
- Key Laboratory of Cosmetics, China National Light Industry, Beijing Technology and Business University, No. 11/33, Fucheng Road, Haidian District, Beijing 100048, PR China; Beijing Key Laboratory of Plant Resources Research and Development, Beijing Technology and Business University, No. 11/33, Fucheng Road, Haidian District, Beijing 100048, PR China
| | - Fan Yi
- Key Laboratory of Cosmetics, China National Light Industry, Beijing Technology and Business University, No. 11/33, Fucheng Road, Haidian District, Beijing 100048, PR China; Beijing Key Laboratory of Plant Resources Research and Development, Beijing Technology and Business University, No. 11/33, Fucheng Road, Haidian District, Beijing 100048, PR China
| | - Hong Meng
- Key Laboratory of Cosmetics, China National Light Industry, Beijing Technology and Business University, No. 11/33, Fucheng Road, Haidian District, Beijing 100048, PR China; Beijing Key Laboratory of Plant Resources Research and Development, Beijing Technology and Business University, No. 11/33, Fucheng Road, Haidian District, Beijing 100048, PR China
| | - Yi-Fan He
- Key Laboratory of Cosmetics, China National Light Industry, Beijing Technology and Business University, No. 11/33, Fucheng Road, Haidian District, Beijing 100048, PR China; Beijing Key Laboratory of Plant Resources Research and Development, Beijing Technology and Business University, No. 11/33, Fucheng Road, Haidian District, Beijing 100048, PR China
| | - Miao-Miao Guo
- Key Laboratory of Cosmetics, China National Light Industry, Beijing Technology and Business University, No. 11/33, Fucheng Road, Haidian District, Beijing 100048, PR China; Beijing Key Laboratory of Plant Resources Research and Development, Beijing Technology and Business University, No. 11/33, Fucheng Road, Haidian District, Beijing 100048, PR China.
| |
Collapse
|
20
|
Raudsepp U, Maljutenko I, Kõuts M, Granhag L, Wilewska-Bien M, Hassellöv IM, Eriksson KM, Johansson L, Jalkanen JP, Karl M, Matthias V, Moldanova J. Shipborne nutrient dynamics and impact on the eutrophication in the Baltic Sea. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 671:189-207. [PMID: 30928749 DOI: 10.1016/j.scitotenv.2019.03.264] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Revised: 03/15/2019] [Accepted: 03/17/2019] [Indexed: 06/09/2023]
Abstract
The Baltic Sea is a severely eutrophicated sea-area where intense shipping as an additional nutrient source is a potential contributor to changes in the ecosystem. The impact of the two most important shipborne nutrients, nitrogen and phosphorus, on the overall nutrient-phytoplankton-oxygen dynamics in the Baltic Sea was determined by using the coupled physical and biogeochemical model system General Estuarine Transport Model-Ecological Regional Ocean Model (GETM-ERGOM) in a cascade with the Ship Traffic Emission Assessment Model (STEAM) and the Community Multiscale Air Quality (CMAQ) model. We compared two nutrient scenarios in the Baltic Sea: with (SHIP) and without nutrient input from ships (NOSHIP). The model uses the combined nutrient input from shipping-related waste streams and atmospheric depositions originating from the ship emission and calculates the effect of excess nutrients on the overall biogeochemical cycle, primary production, detritus formation and nutrient flows. The shipping contribution is about 0.3% of the total phosphorus and 1.25-3.3% of the total nitrogen input to the Baltic Sea, but their impact to the different biogeochemical variables is up to 10%. Excess nitrogen entering the N-limited system of the Baltic Sea slightly alters certain pathways: cyanobacteria growth is compromised due to extra nitrogen available for other functional groups while the biomass of diatoms and especially flagellates increases due to the excess of the limiting nutrient. In terms of the Baltic Sea ecosystem functioning, continuous input of ship-borne nitrogen is compensated by steady decrease of nitrogen fixation and increase of denitrification, which results in stationary level of total nitrogen content in the water. Ship-borne phosphorus input results in a decrease of phosphate content in the water and increase of phosphorus binding to sediments. Oxygen content in the water decreases, but reaches stationary state eventually.
Collapse
Affiliation(s)
- Urmas Raudsepp
- Department of Marine Systems, Tallinn University of Technology, Akadeemia Road 15a, 12618 Tallinn, Estonia.
| | - Ilja Maljutenko
- Department of Marine Systems, Tallinn University of Technology, Akadeemia Road 15a, 12618 Tallinn, Estonia
| | - Mariliis Kõuts
- Department of Marine Systems, Tallinn University of Technology, Akadeemia Road 15a, 12618 Tallinn, Estonia
| | - Lena Granhag
- Department of Mechanics and Maritime Sciences, Chalmers University of Technology, Hörselgången 4, 41756 Gothenburg, Sweden
| | - Magda Wilewska-Bien
- Department of Mechanics and Maritime Sciences, Chalmers University of Technology, Hörselgången 4, 41756 Gothenburg, Sweden
| | - Ida-Maja Hassellöv
- Department of Mechanics and Maritime Sciences, Chalmers University of Technology, Hörselgången 4, 41756 Gothenburg, Sweden
| | - K Martin Eriksson
- Department of Mechanics and Maritime Sciences, Chalmers University of Technology, Hörselgången 4, 41756 Gothenburg, Sweden
| | - Lasse Johansson
- Atmospheric Composition Research, Finnish Meteorological Institute, 00560 Helsinki, Finland
| | - Jukka-Pekka Jalkanen
- Atmospheric Composition Research, Finnish Meteorological Institute, 00560 Helsinki, Finland
| | - Matthias Karl
- Helmholtz-Zentrum Geesthacht, Max-Planck- Straße 1, 21502 Geesthacht, Germany
| | - Volker Matthias
- Helmholtz-Zentrum Geesthacht, Max-Planck- Straße 1, 21502 Geesthacht, Germany
| | - Jana Moldanova
- Swedish Environmental Research Institute, Box 530 21, SE-400 14 Gothenburg, Sweden
| |
Collapse
|