scholarly journals Assessment of Emission Reduction and Meteorological Change in PM2.5 and Transport Flux in Typical Cities Cluster during 2013–2017

2021 ◽  
Vol 13 (10) ◽  
pp. 5685
Author(s):  
Panbo Guan ◽  
Hanyu Zhang ◽  
Zhida Zhang ◽  
Haoyuan Chen ◽  
Weichao Bai ◽  
...  
Keyword(s):  
Air Quality ◽  
Action Plan ◽  
Influence Factors ◽  
Pollution Prevention ◽  
Weather Conditions ◽  
Yangtze River Delta ◽  
Control Measures ◽  
Joint Control ◽  
Air Quality Model ◽  
Quality Model

Under the Air Pollution Prevention and Control Action Plan (APPCAP) implemented, China has witnessed an air quality change during the past five years, yet the main influence factors remain relatively unexplored. Taking the Beijing-Tianjin-Hebei (BTH) and Yangtze River Delta (YRD) regions as typical cluster cities, the Weather Research Forecasting (WRF) and Comprehensive Air Quality Model with Extension (CAMx) were introduced to demonstrate the meteorological and emission contribution and PM2.5 flux distribution. The results showed that the PM2.5 concentration in BTH and YRD significantly declined with a descend ratio of −39.6% and −28.1%, respectively. For the meteorological contribution, those regions had a similar tendency with unfavorable conditions in 2013–2015 (contribution concentration 1.6–3.8 μg/m3 and 1.1–3.6 μg/m3) and favorable in 2016 (contribution concentration −1.5 μg/m3 and −0.2 μg/m3). Further, the absolute value of the net flux’s intensity was positively correlated with the degree of the favorable/unfavorable weather conditions. When it came to emission intensity, the total net inflow flux increased, and the outflow flux decreased significantly across the border with the emission increasing. In short: the aforementioned results confirmed the effectiveness of the regional joint emission control and provided scientific support for the proposed effective joint control measures.

scholarly journals Characteristics and Source Apportionment of PM2.5 and O3 during Winter of 2013 and 2018 in Beijing

Atmosphere ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1324
Author(s):  
Yisheng Zhong ◽  
Xiaoqi Wang ◽  
Shuiyuan Cheng
Keyword(s):  
Air Quality ◽  
Sharp Decrease ◽  
Weather Conditions ◽  
Capital City ◽  
Air Quality Model ◽  
Quality Model ◽  
Hysplit Model ◽  
Control Policies ◽  
Air Mass ◽  
Pm2.5 Concentration

Beijing, the capital city of China, has achieved remarkable progress in terms of an improvement in air quality under strict control policies in the past 10 years from various sources. In this paper, the characteristics of fine particulate matter (PM2.5) and O3 in January 2013 and 2018 in Beijing are discussed on the basis of daily sample analysis and hourly monitoring data. It was found that the PM2.5 pollution for the month of January in Beijing has been greatly curbed. The SO42− concentration and proportion of PM2.5 decreased, while the proportions of NO3− and NH4+ increased. Organic matter represented the major component during the two periods with the proportions of 31.7% ± 8.2% and 31.4% ± 9.8%. The results of the Hybrid Single Particle Lagrangian Integrated Trajectory (Hysplit) model and Potential Source Contribution Function (PSCF) method showed that air mass from southern nearby regions accounted for 34% and 10% in 2013 and 2018, respectively, which was closely related to the pollution period. Thus, the input direction of air mass in January 2018 was more conducive to the diffusion of pollutants. Modeling results of the Weather Research and Forecasting model (WRF) coupled with Comprehensive Air Quality Model Extensions (CAMx) indicated that the contribution of industry sources to PM2.5 and O3 decreased from 2013 to 2018, while mobile sources increased. This was mainly due to the different control policies on various emission sources. In terms of O3 sources, more control measurements should be taken on volatile organic compounds (VOCs) due to its prominent effect on O3 concentration in both periods. The reduction in emissions and the meteorological conditions both contributed effectively to the sharp decrease in PM2.5 concentration. However, the change in weather conditions had the greater impact on the decrease in PM2.5 concentration, while the reduction in emissions was weakened as a function of this change.

Regional source apportionment of ozone and PM2.5 during the EXPLORE-YRD campaign in the Yangtze River Delta region of China

2020 ◽  
Author(s):  
Jianlin Hu ◽  
Lin Li ◽  
Jingyi Li ◽  
Xueying Wang ◽  
Kangjia Gong
Keyword(s):  
Air Quality ◽  
Yangtze River Delta ◽  
River Delta ◽  
Formation Mechanisms ◽  
Aerosol Formation ◽  
Air Quality Model ◽  
Quality Model ◽  
Haze Pollution ◽  
Source Category ◽  
The Yrd

<p>Although the air quality in China has been improved by collaborative efforts dedicating to mitigate the haze pollution, PM2.5 concentrations still remain high levels and the issue of increasing O<sub>3</sub> concentration has attracted more attention of the public. The YRD region has been suffering from both the PM2.5 and O3 pollution problems. To investigate the formation mechanisms and sources of PM2.5 and O3 in this region, a comprehensive EXPLORE-YRD campaign (EXPeriment on the eLucidation of theatmospheric Oxidation capacity and aerosol foRmation, and their Effects inYangtze River Delta) was carried out in May - June 2018. In this study, we investigate the contributions of different source categories to PM2.5 and O<sub>3</sub>. A source-oriented 3-D air quality model (CMAQ) was applied to analyze contributions of different emission sources to PM2.5 and O<sub>3 </sub>in the YRD region. Emissions were divided into eight source categories: industry, power, transportation, residential, agriculture, biogenic, wildfire, and other countries. Contribution from individual source category was quantified. The importance of anthropogenic and natural sources to PM2.5 and O<sub>3</sub> was discussed.</p>

Study on the Countermeasures of NOx Emission Reduction in Chengdu Economic Circle

2013 ◽  
Vol 726-731 ◽  
pp. 2324-2332
Author(s):  
Wen Yong Wang ◽  
Xiao Juan Ma
Keyword(s):  
Air Quality ◽  
Power Plant ◽  
Thermal Power Plant ◽  
Thermal Power ◽  
Ambient Air ◽  
Control Measures ◽  
Cement Plant ◽  
Air Quality Model ◽  
Quality Model ◽  
Mean Concentration

Based on the detailed survey on the source and volume of NOx emission over Chengdu Economic Circle, the third-generation air quality model CMAQ is adopted for simulating the density of NOx in the air over Chengdu Economic Circle. The result shows that the hourly concentration, daily mean concentration and annual mean concentration of NOx in air exceed the standard data, and the affected areas respectively account for 0.2%, 0.18% and 0.12% of the total area of the economic circle. Meanwhile, in accordance with the simulation calculation, The NOX emission of the vehicle exhaust, the thermal power plant and the cement plant are the major NOX concentration contribution sources in air, contribution rate is amounting to 39.13%, 21.41% and 15.34% respectively. Thus, three main measures to reduce the emission of NOx of Chengdu Economic Circle are proposed as follows: firstly, strengthen the management of vehicle and reduce the emission of NOx by the vehicle; secondly, manage the NOx of the industrial enterprise; flue gas denitrification equipment must be constructed in the thermal power plant and cement manufacturing enterprise, and the comprehensive denitration efficiency of the thermal power plant should be not less than 70% and the comprehensive denitration efficiency of the cement plant should not be less than 60%; thirdly, joint prevention and control measures should be implemented between the cities, so as to reduce the transport of NOx. With the application of the above measures, the emission reductions of NOx can be reduced to 55% of the existing volume, and the concentration of NOx in the air can meet with the Class II of national ambient air quality Standard.

scholarly journals The Temporal and Spatial Changes of Ship-Contributed PM2.5 Due to the Inter-Annual Meteorological Variation in Yangtze River Delta, China

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 722
Author(s):  
Dongsheng Chen ◽  
Dingyue Liang ◽  
Lei Li ◽  
Xiurui Guo ◽  
Jianlei Lang ◽  
...  
Keyword(s):  
Air Quality ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
River Delta ◽  
Simultaneous Increase ◽  
Air Quality Model ◽  
Quality Model ◽  
Meteorological Variation ◽  
Annual Changes ◽  
The Impact

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.

scholarly journals Identification Source of Variation on Regional Impact of Air Quality Pattern using Chemometric Techniques in Kuching, Sarawak

2018 ◽  
Vol 7 (3.14) ◽  
pp. 49
Author(s):  
Nur Liyana Zakri ◽  
Ahmad Shakir Mohd Saudi ◽  
Hafizan Juahir ◽  
Mohd Ekhwan Toriman ◽  
Izuddin Fahmy Abu ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Human Health ◽  
Action Plan ◽  
Strong Positive Correlation ◽  
Air Quality Model ◽  
Quality Model ◽  
Statistical Process ◽  
Regional Impact ◽  
Chemometric Techniques

Air pollution has been considered a devastating environmental issue that can negatively impact human health and the environment. Kuching as one of the capital cities in Malaysia is also affected by air pollution and unsatisfactory air quality condition. Thus, the main objective is to identify the source of variation on regional impact of air quality pattern in Kuching, Sarawak. A seven-year (2009-2015) database was acquired from the Malaysia Department of Environment (DOE). The data were analysed using several Chemometric Techniques. The findings demonstrated strong positive correlation of Particulate Matter below than 10 microns (PM10) and API (r = 0.994). In addition, Principal Component Analysis (PCA) and Artificial Neural Network (ANN) revealed that Carbon Monoxide (CO), Ozone (O3) and PM10 were the most significant air pollutants in Kuching. Based on the results in the Statistical Process Chart (SPC) analysis, PM10,COand O3 values exceeded the Control Limit (CL) of SPC. This study concluded that the application of air quality model in this study is relevant for mitigating action plan of air quality in Kuching, Sarawak, as it is of paramount importance to continuously monitor and manage the quality of air for the sustainability of the environment and human health.  

Use of a Dynamic Air Quality Model to Reduce the Uncertainties of Seasonal and Annual Atmospheric Depositions for Mercury TMDLs

2005 ◽  
Vol 2005 (3) ◽  
pp. 1393-1414
Author(s):  
Kuo-Liang Lai ◽  
Janet Kremer ◽  
Susan Sciarratta ◽  
R. Dwight Atkinson ◽  
Tom Myers
Keyword(s):  
Air Quality ◽  
Air Quality Model ◽  
Quality Model ◽  
Atmospheric Depositions

The Message of “APEC Blue” for the Prevention and Control of Urban Air Pollution in China

2016 ◽  
Vol 04 (04) ◽  
pp. 1650027
Author(s):  
Rong ZHU
Keyword(s):  
Air Pollution ◽  
Emergency Response ◽  
Prevention And Control ◽  
Urban Air Pollution ◽  
Pollution Prevention ◽  
Warning System ◽  
Weather Conditions ◽  
Control Measures ◽  
Atmospheric Pollutant ◽  
And Control

Analysis of the meteorological conditions for atmospheric pollutant dispersion before and after the 2014 APEC meeting shows very significant effects of air pollution prevention and control measures on the meeting. It proves that the proper measures to control air pollution in the Beijing-Tianjin-Hebei Region are: establishing a regional emergency response mechanism to reduce emissions in the case of heavy air pollution, strengthening the local emergency response measures for emission reduction, and enhancing the early warning system for weather conditions conducive to heavy air pollution.

A contribution to the air quality impact assessment of a roadway in Lisbon. The air quality model APOLO

1993 ◽  
Vol 134 (1-3) ◽  
pp. 1-7 ◽  
Author(s):  
Ana Isabel A. Miranda ◽  
Miguel S. Conceição ◽  
Carlos S. Borrego
Keyword(s):  
Air Quality ◽  
Impact Assessment ◽  
Air Quality Model ◽  
Quality Model

scholarly journals Ensemble Predictions of Air Pollutants in China in 2013 for Health Effects Studies Using WRF/CMAQ Modeling System with Four Emission Inventories

2017 ◽  
Author(s):  
Jianlin Hu ◽  
Xun Li ◽  
Lin Huang ◽  
Qi Ying ◽  
Qiang Zhang ◽  
...  
Keyword(s):  
Air Quality ◽  
Health Effects ◽  
Air Pollutants ◽  
Emission Inventory ◽  
Model Performance ◽  
Observation Data ◽  
Emission Inventories ◽  
Air Quality Model ◽  
Quality Model ◽  
Future Health

Abstract. Accurate exposure estimates are required for health effects analyses of severe air pollution in China. Chemical transport models (CTMs) are widely used tools to provide detailed information of spatial distribution, chemical composition, particle size fractions, and source origins of pollutants. The accuracy of CTMs' predictions in China is largely affected by the uncertainties of public available emission inventories. The Community Multi-scale Air Quality model (CMAQ) with meteorological inputs from the Weather Research and Forecasting model (WRF) were used in this study to simulate air quality in China in 2013. Four sets of simulations were conducted with four different anthropogenic emission inventories, including the Multi-resolution Emission Inventory for China (MEIC), the Emission Inventory for China by School of Environment at Tsinghua University (SOE), the Emissions Database for Global Atmospheric Research (EDGAR), and the Regional Emission inventory in Asia version 2 (REAS2). Model performance was evaluated against available observation data from 422 sites in 60 cities across China. Model predictions of O3 and PM2.5 with the four inventories generally meet the criteria of model performance, but difference exists in different pollutants and different regions among the inventories. Ensemble predictions were calculated by linearly combining the results from different inventories under the constraint that sum of the squared errors between the ensemble results and the observations from all the cities was minimized. The ensemble annual concentrations show improved agreement with observations in most cities. The mean fractional bias (MFB) and mean fractional errors (MFE) of the ensemble predicted annual PM2.5 at the 60 cities are −0.11 and 0.24, respectively, which are better than the MFB (−0.25–−0.16) and MFE (0.26–0.31) of individual simulations. The ensemble annual 1-hour peak O3 (O3-1 h) concentrations are also improved, with mean normalized bias (MNB) of 0.03 and mean normalized errors (MNE) of 0.14, compared to MNB of 0.06–0.19 and MNE of 0.16–0.22 of the individual predictions. The ensemble predictions agree better with observations with daily, monthly, and annual averaging times in all regions of China for both PM2.5 and O3-1 h. The study demonstrates that ensemble predictions by combining predictions from individual emission inventories can improve the accuracy of predicted temporal and spatial distributions of air pollutants. This study is the first ensemble model study in China using multiple emission inventories and the results are publicly available for future health effects studies.

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