Impact of Use of Chemical Transformation Modules in Calpuff on the Results of Air Dispersion Modelling

Oleniacz, Robert; Rzeszutek, Mateusz; Bogacki, Marek

doi:10.1515/eces-2016-0043

Cited by 6 publications

(6 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To identify whether the ammonia is sufficient, the ammonium-to-sulfate ratio (Ratio A-to-S ) is calculated with the published data as well. It is reported that the North China Plain experienced ammonia insufficiency during summer (Ratio A-to-S : less than 1.5), limiting the formation and partitioning of nitrate into the particle phase (Pathak et al, 2004(Pathak et al, , 2009(Pathak et al, , 2011. However, Ratio A-to-S in Beijing during winter was always above 1.5.…”

Section: Comparison Of Major Inorganic Compositions During the Early mentioning

confidence: 99%

Nitrate-dominated PM2.5 and elevation of particle pH observed in urban Beijing during the winter of 2017

Xie

Wang

et al. 2020

Atmos. Chem. Phys.

View full text Add to dashboard Cite

Abstract. The Chinese government has exerted strict emission controls to mitigate air pollution since 2013, which has resulted in significant decreases in the concentrations of air pollutants such as SO2. Strict pollution control actions also reduced the average PM2.5 concentration to the low level of 39.7 µg m−3 in urban Beijing during the winter of 2017. To investigate the impact of such changes on the physiochemical properties of atmospheric aerosols in China, we conducted a comprehensive observation focusing on PM2.5 in Beijing during the winter of 2017. Compared with the historical record (2014–2017), SO2 decreased to the low level of 3.2 ppbv in the winter of 2017, but the NO2 level was still high (21.4 ppbv in the winter of 2017). Accordingly, the contribution of nitrate (23.0 µg m−3) to PM2.5 far exceeded that of sulfate (13.1 µg m−3) during the pollution episodes, resulting in a significant increase in the nitrate-to-sulfate molar ratio. The thermodynamic model (ISORROPIA II) calculation results showed that during the PM2.5 pollution episodes particle pH increased from 4.4 (moderate acidic) to 5.4 (more neutralized) when the molar ratio of nitrate to sulfate increased from 1 to 5, indicating that aerosols were more neutralized as the nitrate content elevated. Controlled variable tests showed that the pH elevation should be attributed to nitrate fraction increase other than crustal ion and ammonia concentration increases. Based on the results of sensitivity tests, future prediction for the particle acidity change was discussed. We found that nitrate-rich particles in Beijing at low and moderate humid conditions (RH: 20 %–50 %) can absorb twice the amount of water that sulfate-rich particles can, and the nitrate and ammonia with higher levels have synergetic effects, rapidly elevating particle pH to merely neutral (above 5.6). As moderate haze events might occur more frequently under abundant ammonia and nitrate-dominated PM2.5 conditions, the major chemical processes during haze events and the control target should be re-evaluated to obtain the most effective control strategy.

show abstract

Section: Comparison Of Major Inorganic Compositions During the Early mentioning

confidence: 99%

Nitrate-dominated PM2.5 and elevation of particle pH observed in urban Beijing during the winter of 2017

Xie

Wang

et al. 2020

Atmos. Chem. Phys.

View full text Add to dashboard Cite

show abstract

“…Particle acidity has widely been studied due to its important roles in haze formation, and is widely implemented in major models (Yu et al, 2005;Robert et al, 2016). Since there was rarely practical method to direct measure the acidity of particles in real atmosphere (Wei et al, 2018;Freedman et al, 2019), calculation of the particle pH by thermodynamic models had been the most used method to quantify particle acidity.…”

Section: Introductionmentioning

confidence: 99%

Observation of nitrate dominant PM2.5 and particle pH elevation in urban Beijing during the winter of 2017

Xie¹,

Wang²,

Wang³

et al. 2019

Preprint

View full text Add to dashboard Cite

Particle acidity is crucial to understand secondary formation processes in pollution events since acidity has substantial impacts on the physiochemical properties of PM2.5. Quantification of particle acidity with simulated pH yielded various values range from 0-7 and conflicting conclusions on sulfate formation mechanisms in China 15 recently. In this article, we found that particle pH could increase to near neutral (5.4) as a result of effective sulfur emission control. Benefit from strict pollution control actions, average PM2.5 concentration reduced to a low level (39.7μg/m 3 ) in urban Beijing during winter of 2017. Compare to history record (2014-2017), SO2 gradually decreased to a low level (3.2ppbv in 2017 winter) while NO2 kept increasing (21.4ppbv in 2017 winter). As a response, nitrate's contribution (23.0μg/m 3 ) to PM2.5 become dominant over sulfate (13.1μg/m 3 ) during PM2.5 20 pollution episodes. The nitrate to sulfate molar ratio significantly increased from 1 to 2.7 (value of 1999 and 2017).As nitrate's fraction significantly elevated, particle pH was also found to increase in winter Beijing given sufficient ammonia (average concentration 7.1μg/m 3 , 12.9μg/m 3 during pollution). During PM2.5 pollution episodes, the particle pH predicted increased from 4.4 (moderate acidic) to 5.4 (near neutral) as nitrate to sulfate molar ratio increased from 1 to 5. It is found that the major H + contributor S(VI) was mostly in the form of sulfate, indicating 25 that anions were more neutralized as nitrate content elevated. In the final part, future prediction of particle acidity change was discussed via sensitivity tests: On one hand, nitrate rich particles would absorb more water compared to the sulfate rich particles. This absorption contrast doubles with low to moderate RH (20%~50%). On the other hand, increased level of nitrate and ammonia would have synergetic effects leading to rapid elevation of particle pH to merely neutral (above 5.6). As moderate haze might occur more frequently with high ammonia and particulate 30 nitrate concentration, the major chemical processes during haze events and the control target shall be re-evaluated to obtain the most effective control strategy.

show abstract

“…Poor air quality in Krakow, often observed during the heating season, is usually associated with unfavorable synoptic-scale (anti-cyclonic circulation), low temperature, low mixing-layer height and low wind speed, which hinders the dispersion of pollutants in the air [58,60,61,64,65], and in the case of fine solid particles with increased formation of secondary inorganic (SIA) or organic (SOA) aerosols [62,[68][69][70][71] and a large inflow background of dust pollution from adjacent areas [22,24,65,67]. Despite a significant reduction of SIA precursor emissions from large combustion plants (SO 2 and NO x ) and residential heating (SO 2 ), the contribution of SIA formation in fine particulate matter is now much greater [68][69][70] than it has been reported for several years ago [72,73]; this indicates an increase in the role of NO x (derived from combustion processes, including to a large extent from the combustion of engine fuels) in the formation of SIA, and thus their greater impact on the levels of fine particulate matter in the air [91,92,97].…”

Section: Discussionmentioning

confidence: 99%

“…Moreover, many other studies present long-term trends in changes of air pollutants concentrations in Krakow and their impact on health [74][75][76][77][78][79][80][81][82], the mineralogical composition and microbiological characteristics of aerosols [83,84], the oxidative potential of PM 10 and PM 2.5 [85], the chemical composition of street dust [86] and dry and wet deposition [87][88][89]. The results of measurements from the automatic air quality monitoring station in Krakow were also used to prepare the pollution background necessary in the process of air pollution modeling and the assessment or validation of the dispersion [90][91][92][93][94][95][96][97] or prognostic [98][99][100][101] models used.…”

Section: Introductionmentioning

confidence: 99%

Assessment of the Variability of Air Pollutant Concentrations at Industrial, Traffic and Urban Background Stations in Krakow (Poland) Using Statistical Methods

Oleniacz

Gorzelnik

2021

Sustainability

Self Cite

View full text Add to dashboard Cite

In cities with an extensive air quality monitoring (AQM) system, the results of pollutant concentration measurements obtained in this system can be used not only for current assessments of air pollution, but also for analyzes aimed at better identification of factors influencing the air quality and for tracking trends in changes taking place in this regard. This can be achieved with the use of statistical methods that allow for the assessment of the variability of measurement data observed at stations of various types and for the determination of possible interdependencies between these data. In this article, an analysis of this type was carried out for traffic, urban background and industrial AQM stations in Krakow (Southern Poland) operating in the years 2017–2018 with the use of, i.a., cluster analyzes, as well as dependent samples t-test and Wilcoxon signed-rank test, taking into account the concentrations of air pollutants such as fine particulate matter (PM10), nitrogen dioxide (NO2), benzene (C6H6) and sulfur dioxide (SO2). On the basis of the conducted analyzes, similarities and differences were shown between the data observed at individual types of stations, and the possibilities of using them to identify the causes of the observed changes and the effects of remedial actions to improve air quality undertaken recently and planned in the future were indicated. It was found that the air concentrations of some substances measured at these stations can be used to assess the emission abatement effects in road transport (NO2, PM10 or C6H6), residential heating (PM10 or SO2), and selective industrial plants (SO2, NO2 or C6H6).

show abstract

Impact of Use of Chemical Transformation Modules in Calpuff on the Results of Air Dispersion Modelling

Cited by 6 publications

References 32 publications

Nitrate-dominated PM<sub>2.5</sub> and elevation of particle pH observed in urban Beijing during the winter of 2017

Nitrate-dominated PM<sub>2.5</sub> and elevation of particle pH observed in urban Beijing during the winter of 2017

Observation of nitrate dominant PM<sub>2.5</sub> and particle pH elevation in urban Beijing during the winter of 2017

Assessment of the Variability of Air Pollutant Concentrations at Industrial, Traffic and Urban Background Stations in Krakow (Poland) Using Statistical Methods

Contact Info

Product

Resources

About

Impact of Use of Chemical Transformation Modules in Calpuff on the Results of Air Dispersion Modelling

Cited by 6 publications

References 32 publications

Nitrate-dominated PM&lt;sub&gt;2.5&lt;/sub&gt; and elevation of particle pH observed in urban Beijing during the winter of 2017

Nitrate-dominated PM&lt;sub&gt;2.5&lt;/sub&gt; and elevation of particle pH observed in urban Beijing during the winter of 2017

Observation of nitrate dominant PM&lt;sub&gt;2.5&lt;/sub&gt; and particle pH elevation in urban Beijing during the winter of 2017

Assessment of the Variability of Air Pollutant Concentrations at Industrial, Traffic and Urban Background Stations in Krakow (Poland) Using Statistical Methods

Contact Info

Product

Resources

About

Nitrate-dominated PM<sub>2.5</sub> and elevation of particle pH observed in urban Beijing during the winter of 2017

Nitrate-dominated PM<sub>2.5</sub> and elevation of particle pH observed in urban Beijing during the winter of 2017

Observation of nitrate dominant PM<sub>2.5</sub> and particle pH elevation in urban Beijing during the winter of 2017