Source apportionment of fine particulate matter in China in 2013 using a source-oriented chemical transport model

Shi, Zhihao; Li, Jingyi; Huang, Lin; Wang, Peng; Wu, Li; Ying, Qi; Zhang, Hongliang; Li, Lu; Liu, Xuejun; Liao, Hong; Hu, Jianlin

doi:10.1016/j.scitotenv.2017.06.019

Cited by 100 publications

(56 citation statements)

References 60 publications

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“…This version of the sourceoriented CMAQ is capable of simultaneously tracking both primary particulate matter (PPM) and secondary inorganic aerosol (SIA, including ammonia (NH4 + ), NO3 − , and SO4 2− ) from multiple source sectors and regions. It unifies the two previous models individually developed for PPM (Hu et al, 2015) and SIA (Ying et al, 2014;Shi et al, 2017) into a single consistent model framework. For SIA, multiple source-tagged reactive species are introduced in both gas and particle phases to represent the same species originated from different source sectors or regions.…”

Section: Model Descriptionmentioning

confidence: 88%

“…Remote sensing has been used to show the transport of dust storms (Uno et al, 2009) and wildfire plumes (Wu et al, 2018), but it cannot quantitatively determine source-region contributions. CTMs have also been used to quantify contributions from different regions and sectors to air pollutants for areas at local to global scales (Lelieveld et al, 2015;Shi et al, 2017;Kim et al, 2015;Bove et al, 2014;Itahashi et al, 2017). Sensitivity analysis and tagged-tracer methods are the main types of methods used in CTMs to quantify source contributions (Burr and Zhang, 2011).…”

Section: Introductionmentioning

confidence: 99%

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

Xue¹,

Guo²,

Ya³

et al. 2019

Preprint

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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.

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Section: Model Descriptionmentioning

confidence: 88%

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

Self Cite

View full text Add to dashboard Cite

show abstract

“…This version of the source-oriented CMAQ is capable of simultaneously tracking both primary particulate matter (PPM) and secondary inorganic aerosols (SIA, including NH + 4 , NO − 3 , and SO 2− 4 ) from multiple source sectors and regions. It unifies the two previous models individually developed for PPM (Hu et al, 2015) and SIA (Ying et al, 2014;Shi et al, 2017) into a single consistent model framework. For SIA, multiple source-tagged reactive species are introduced in both gas and particle phases to represent the same species originated from different source sectors or regions.…”

Section: Model Descriptionmentioning

confidence: 94%

“…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%

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.

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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.

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“…To quantify source contributions to PM2.5 and other air pollutants at a regional or national level, atmospheric chemistrytransport models can be applied (e.g. Ying et al, 2014;Hu et al, 2015;Wang et al, 2015;Shi et al, 2017;Timmermans et al, 2017;Qiao et al, 2018) using two main methods. The first method uses a "tagging" approach (also referred to as a "sourceattribution" or "source-oriented" approach), where species in the model are tagged to trace the origin of the air pollutant of interest.…”

mentioning

confidence: 99%

Exploring the impacts of anthropogenic emission sectors on PM2.5 and human health in South and East Asia

Reddington¹,

Conibear²,

Knote³

et al. 2019

Preprint

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Abstract. To improve poor air quality in Asia and inform effective emission-reduction strategies, it is vital to understand the contributions of different pollution sources and their associated human health burdens. In this study, we use the WRF-Chem regional atmospheric model to explore the air quality and human health benefits of eliminating emissions from seven different anthropogenic sectors (transport, industry, shipping, agriculture, energy generation, residential combustion and open biomass burning) over South and East Asia in 2014. We evaluate WRF-Chem against measurements from air quality monitoring stations across the region and find the model captures the spatial distribution and magnitude of PM2.5 (particulate matter <&#8201;2.5&#8201;&#181;m diameter). We find that eliminating emissions from residential energy use, industry or open biomass burning yield the largest reductions in population-weighted PM2.5 concentrations across the region. The largest human health benefit is achieved by eliminating either residential or industrial emissions, averting 467&#8201;000 (409&#8201;000&#8211;542&#8201;000) or 283&#8201;000 (95UI: 226&#8201;000&#8211;358&#8201;000) annual premature mortalities, respectively in India, China and Southeast Asia; with fire prevention averting 28&#8201;000 (95UI: 24&#8201;000&#8211;32&#8201;000) annual premature mortalities across the region. We compare our results to previous sector-specific emission studies. Across these studies, residential emissions are the dominant cause of particulate pollution in India, with a multi-model mean contribution of 42&#8201;% to population-weighted annual mean PM2.5. Residential and industrial emissions cause the dominant contributions in China, with multi-model mean contributions of 29&#8201;% for both sectors to population-weighted annual mean PM2.5. Future work should focus on identifying the most effective options within the residential, industrial and open biomass burning emission sectors to improve air quality across South and East Asia.

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Source apportionment of fine particulate matter in China in 2013 using a source-oriented chemical transport model

Cited by 100 publications

References 60 publications

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

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

Exploring the impacts of anthropogenic emission sectors on PM<sub>2.5</sub> and human health in South and East Asia

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Source apportionment of fine particulate matter in China in 2013 using a source-oriented chemical transport model

Cited by 100 publications

References 60 publications

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

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

Exploring the impacts of anthropogenic emission sectors on PM&lt;sub&gt;2.5&lt;/sub&gt; and human health in South and East Asia

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Exploring the impacts of anthropogenic emission sectors on PM<sub>2.5</sub> and human health in South and East Asia