Numerical simulations for the sources apportionment and control strategies of PM2.5 over Pearl River Delta, China, part I: Inventory and PM2.5 sources apportionment

Huang, Yeqi; Deng, Tao; Li, Zhenning; Wang, Nan; Yin, C.Q.; Wang, Shiqiang; Fan, Saijun

doi:10.1016/j.scitotenv.2018.04.208

Cited by 55 publications

(27 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…By using the WRF-CMAQ Model, Huang et al studied the source apportionment of PM 2.5 in the dry season (November 2010) of the PRD region and adopted the Brute-Force method (BFM) to simulate the contribution of different regions to the PM 2.5 pollution in this region. They found that local emissions are important contributors to the PM 2.5 pollution in Guangzhou and Foshan; meanwhile, emissions from Dongguan and Huizhou also contribute to the PM 2.5 pollution in Guangzhou; while emissions in Guangzhou, Dongguan and Huizhou are major contributors to the PM 2.5 pollution in Foshan [51].…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Air Quality and the Effect of Governance Policies in China’s Pearl River Delta, 2015–2018

Gao

Yang

et al. 2019

Atmosphere

View full text Add to dashboard Cite

The evaluation of China’s air pollution and the effectiveness of its governance policies is currently a topic of general concern in the academic community. We have improved the traditional evaluation method to construct a comprehensive air quality assessment model based on China’s major air pollutants. Using the daily air pollutant data of 2015–2018, we calculated and analyzed the monthly air quality of nine cities in the Pearl River Delta of China, and conducted a comparative study on the effect of the air pollution control policies of the cities in the Pearl River Delta. We found that the air quality control policies in those nine cities were not consistent. Specifically, the pollution control policies of Guangzhou and Foshan have achieved more than 20% improvement. The pollution control policies of Dongguan and Zhaoqing have also achieved more than 10% improvement. However, due to the relative lag of the formulation and implementation of air pollution control policies, the air quality of Jiangmen, Zhuhai and Zhongshan has declined. Based on the analysis of the air quality assessment results and the effects of governance policies in each city during the study period, we propose suggestions for further improvement of the effectiveness of air pollution control policies in the region.

show abstract

Section: Introductionmentioning

confidence: 99%

Analysis of the Air Quality and the Effect of Governance Policies in China’s Pearl River Delta, 2015–2018

Gao

Yang

et al. 2019

Atmosphere

View full text Add to dashboard Cite

show abstract

“…Sensitivity analysis and tagged-tracer methods are the main types of methods used in CTMs to quantify source contributions (Burr and Zhang, 2011). Sensitivity analysis such as the brute-force method is more suitable to estimate air quality changes due to emission perturbations, as emissions from certain sources would be eliminated or reduced in each simulation of sensitivity analysis (Burr and Zhang, 2011;Huang et al, 2018;Han et al, 2018). In the tagged-tracer method, source-tagged-species are used to track air pollutants from Atmos.…”

Section: Introductionmentioning

confidence: 99%

Local and regional contributions to fine particulate matter in the 18 cities of Sichuan Basin, southwestern China

Xue¹,

Guo²,

Ya³

et al. 2019

Preprint

View full text Add to dashboard Cite

Abstract. The Sichuan Basin (SCB) is one of the regions suffering from severe air pollution in China, but fewer studies have been conducted for this region than the more developed regions in North and East China. In this study, a source-oriented version of the Community Multi-scale Air Quality (CMAQ) model was used to quantify contributions from nine regions to PM2.5 (i.e., particulate matter (PM) with an aerodynamic diameter less than 2.5&#8201;&#956;m) and its components in the 18 cities within the SCB in the winter (December 2014 to February 2015) and summer (June to August, 2015). In the winter, citywide average PM2.5 concentrations are 45~126&#8201;&#956;g&#8201;m&#8722;3, with 21~51&#8201;% and 39~66&#8201;% due to local and non-local emissions, respectively. In the summer, 15~45&#8201;% and 25~52&#8201;% of citywide average PM2.5 (14~31&#8201;&#956;g&#8201;m&#8722;3) are due to local and non-local emissions, respectively. Compared to primary PM (PPM), the inter-region transport of secondary inorganic aerosols (SIA, including ammonia (NH4+), nitrate (NO3&#8722;), and sulfate (SO42&#8722;)) is greater. The region to the east of SCB (R7) is the largest contributor outside the SCB, and it can contribute approximately 80&#8201;% in the northeast, east, and southeast rims of the SCB, but only 10&#8201;% in the other regions in both seasons. Under favorable transport conditions, regional transport of air pollutants from R7 could account for up to 35~100&#8201;&#956;g&#8201;m&#8722;3 of PM2.5 in each of the SCB cities in the winter. This study demonstrates that it is important to have joint emission control efforts among cities within the SCB and neighbor regions to the east in order to reduce PM2.5 concentrations and prevent high PM2.5 days for the entire basin.

show abstract

“…Remote-sensing and air parcel trajectory models, such as the Potential Source Contribution Function (PSCF) and the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) can only reflect the atmospheric dynamics, so they are not quantitative for source apportionment of secondary species (Begum et al, 2005;Uno et al, 2009;Stein et al, 2015;Liu et al, 2018;Wu et al, 2018). Compared to above methods, CTMs are more quantitative, as they can track the source contributions to both primary and secondary air pollutants from a specific region or sectorial source for studies at the local, regional, or global scale (Bove et al, 2014;Kim et al, 2015;Lelieveld et al, 2015;Itahashi et al, 2017;Shi et al, 2017). In CTMs, source contributions are quantified through two methods, namely, sensitivity analysis and tagged-tracer methods (Burr and Zhang, 2011).…”

mentioning

confidence: 99%

“…In CTMs, source contributions are quantified through two methods, namely, sensitivity analysis and tagged-tracer methods (Burr and Zhang, 2011). Sensitivity analysis such as the brute-force method is more suitable to estimate air quality changes due to emission perturbations, as emissions from certain sources would be eliminated or reduced in each simulation of sensitivity analysis (Burr and Zhang, 2011;Han et al, 2018;Huang et al, 2018). In the tagged-tracer method, source-tagged species are used to track air pollutants from specific emission regions and sectors, and they go through all of the nonlinear chemical and physical processes in the model, and thus this method is considered to provide more realistic evaluations of the contributions of different source sectors or source regions to the current level of air pollution under the current emission intensity (Wang et al, 2009;Burr and Zhang, 2011;Chen et al, 2017).…”

mentioning

confidence: 99%

Local and regional contributions to fine particulate matter in the 18 cities of Sichuan Basin, southwestern China

Qiao

Guo

et al. 2019

Atmos. Chem. Phys.

View full text Add to dashboard Cite

Abstract. The Sichuan Basin (SCB) is one of the regions suffering from severe air pollution in China, but fewer studies have been conducted for this region than for the more developed regions in eastern and northern China. In this study, a source-oriented version of the Community Multiscale Air Quality (CMAQ) model was used to quantify contributions from nine regions to PM2.5 (i.e., particulate matter, PM, with an aerodynamic diameter less than 2.5 µm) and its components in the 18 cities within the SCB in the winter (December 2014 to February 2015) and summer (June to August 2015). In the winter, citywide average PM2.5 concentrations are 45–126 µg m−3, with 21 %–51 % and 39 %–66 % being due to local and nonlocal emissions, respectively. In the summer, 15 %–45 % and 25 %–52 % of citywide average PM2.5 (14–31 µg m−3) are due to local and nonlocal emissions, respectively. Compared to primary PM (PPM), the inter-region transport of secondary inorganic aerosols (SIA), including ammonia, nitrate, and sulfate ions (NH4+, NO3-, and SO42-, respectively), and their gas-phase precursors are greater. The region to the east of SCB (R7, including central and eastern China and others) is the largest contributor outside the SCB, and it can contribute approximately 80 % of PM2.5 in the eastern, northeastern, and southeastern rims of the SCB but only 10 % in other SCB regions in both seasons. Under favorable transport conditions, regional transport of air pollutants from R7 could account for up to 35–100 µg m−3 of PM2.5 in each of the SCB cities in the winter. This study demonstrates that it is important to have joint emission control efforts among cities within the SCB and regions to the east in order to reduce PM2.5 concentrations and prevent high PM2.5 days for the entire basin.

show abstract

Numerical simulations for the sources apportionment and control strategies of PM2.5 over Pearl River Delta, China, part I: Inventory and PM2.5 sources apportionment

Cited by 55 publications

References 30 publications

Analysis of the Air Quality and the Effect of Governance Policies in China’s Pearl River Delta, 2015–2018

Analysis of the Air Quality and the Effect of Governance Policies in China’s Pearl River Delta, 2015–2018

Local and regional contributions to fine particulate matter in the 18 cities of Sichuan Basin, southwestern China

Local and regional contributions to fine particulate matter in the 18 cities of Sichuan Basin, southwestern China

Contact Info

Product

Resources

About