the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Quantifying the seasonal variations and regional transport of PM2.5 in the Yangtze River Delta region, China: Characteristics, sources, and health risks
Yangzhihao Zhan
Tijian Wang
Pulong Chen
Jun Tian
Kuanguang Zhu
Yi Luo
Runqi Zhao
Shu Li
Bingliang Zhuang
Mengmeng Li
Abstract. Given the increasing complexity of the chemical composition of PM2.5, identifying and quantitatively assessing the contributions of pollution sources has played an important role in formulating policies to control particle pollution. This study provides a comprehensive assessment between PM2.5 chemical characteristics, sources, and health risks based on sampling data conducted over one year (March 2018 to February 2019) in Nanjing. Results show that PM2.5 exhibits a distinct variation across different seasons, which is primarily driven by emissions, meteorological conditions, and chemical conversion of gaseous pollutants. First, the chemical mass reconstruction shows that secondary inorganic aerosols (SIA, 62.5 %) and carbonaceous aerosols (21.3 %) contributed most to the PM2.5 mass. The increasing oxidation rates of SO2 and NO2 from summer to winter indicate that the secondary transformation of gaseous pollutants is strongly positively correlated with relative humidity. Second, the positive matrix factorization (PMF) method shows that identified PM2.5 sources include SIA (42.5 %), coal combustion (CC, 22.4 %), industry source (IS, 17.3 %), vehicle emission (VE, 10.7 %), fugitive dust (FD, 5.8 %) and other sources (1.3 %). The Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and the concentration-weighted trajectory (CWT) analysis are used to further explore different spatial distributions and regional transport of sources. High emissions (10-11 μg·m−3) of SIA and CC distribute in Nanjing and central China in winter. Moderate emissions (8-9 μg·m−3) of IS and VE are potentially located in the north of Jiangsu, Anhui, and Jiangxi. The PM2.5 pollution from long-range transport is attenuated by meteorological conditions and ocean air masses. Finally, the health risk assessment indicates that the carcinogenic and non-carcinogenic risks of toxic elements (Cr, As, Ni, Mn, V, and Pb) mainly come from IS, VE, and CC, which are within the tolerance or acceptable level. Although the main source of pollution in Nanjing is SIA at present, we should pay more attention to the health burden of vehicle emissions, coal combustion, and industrial processes.
Yangzhihao Zhan et al.
Status: final response (author comments only)
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RC1: 'Comment on egusphere-2023-489', Anonymous Referee #1, 25 Apr 2023
Particle pollution is of great concern in many areas of East Asia. The Yangtze River Delta region in China is one of these typical highly polluted areas. This paper investigates the source apportionment of PM2.5 by applying positive matrix factorization based on a regional background site in the Yangtze River Delta region and pays attention to the health burden of PM2.5 pollution. The topic and some findings are fascinating. This manuscript not only provides some phenomena but also is a good job of explaining the mechanism. In all, the manuscript can be considered to be published after minor revision. The specific comments are listed below:
(1) The English should be checked and polished.
(2) In Introduction
On lines 52-53, “Air exposure models have been widely used to further assess the non-carcinogenic and carcinogenic health risks of toxic elements in PM2.5”. The source apportionment and health risk of PM2.5 pollution is the focus of this study, and the health risk assessment of this study should conduct a brief description.
In the second and third paragraphs of the introduction section, the authors introduce the chemical components of PM2.5 and the source apportionment methods in a scientific way. The authors summarize and analyze the shortcomings and advantages of relevant literature researches worldwide. However, more papers about air pollution in China should be added to support the ideas in the introduction. For example,
(references)
(3) In Data and Methodology
In Section 2.1, the author introduces detailed information on the sampling and measuring instruments. Whether there are parallel and blank sampling in this study. How about the distribution of pollution sources around the sampling site?
On lines 132-133, “Second, we calculated the uncertainty (Unc) for each species based on the concentration fraction and MDL.” How to set the uncertainty of different data? Detailed formulas on the Unc and MDL are lacking.
On lines 156-157, “The CWT method divided the research area into small equal grids, set a standard value for the research object, and defined the trajectory exceeding the standard value as the pollution trajectory.” It is necessary to present the standard value of the research object in this study. Why use this standard value?
(4) In Results and discussions
On lines 247-248, “meteorological conditions provided favorable conditions for the transformation of gaseous precursors.” There are many factors affecting the oxidation rate of gaseous precursors of PM2.5. In addition to relative humidity, meteorological factors such as temperature, radiation intensity, and boundary layer height all have a significant impact on oxidation rates. Please further explain the reason. For example, comparing the correlation coefficients of PM2.5 with the main meteorological factors in different seasons.
On Line 261, please add the meaning of “C”, “MP”, and “HP” in Fig. 2.
On Lines 338-339, “However, the industrial pollution derived from long-range transport was attenuated by meteorological conditions.” Which meteorological factors had the impacts? I think this needs to be explained in the text.
In Section 3.4, the author investigated the non-carcinogenic and the carcinogenic risks in PM2.5 and their total health risk in each source in Nanjing. The conclusion in this section should be compared with similar studies in other regions. Please briefly describe or cite some papers.
(5) In Conclusions
On lines 375-377, “Based on values of NO3−/SO42− and OC/EC ratio, dominant vehicle emission occurred during the heavily polluted period, and the contribution of coal combustion increased in winter.” The specific rate data should be given.
Citation: https://doi.org/10.5194/egusphere-2023-489-RC1 -
RC2: 'Comment on egusphere-2023-489', Anonymous Referee #2, 27 Apr 2023
This paper presents the source contribution of PM2.5 in a heavily polluted area in China based on measurement of concentrations of PM components at high time resolution. Main source areas of the PM Factors identified are estimated by Backward trajectory analyses. Based on the concentrations measured of potentially toxic elements, carcinogenic and non-carcinogenic risk of these elements is estimated, identifying the sources with a higher potential impact on health.
Results presented in the manuscript are of high interest. In general, the methodology and interpretation of results is sound. However, the major issue of this paper is related to the writing. It should be thoroughly reviewed. Some parts must be reordered. The description should follow a clear order that facilitates understanding. many of the statements are not correctly augmented. There are missing references. Below I have a list of minor corrections (although it is not intended to be an exhaustive list).
Abstract
Lines 23-24. It is confusing; you are discussing about emissions showing values of ambient concentrations. Moreover, what is the limit between high and moderate?
Lines 25-27. Please, check sentence
Line 27. SIA cannot be considered as a source of pollution; SIA accounts for secondary inorganic compounds that can be emitted by a variety of sources. PMF grouped these components given to their major secondary origin and similar formation processes by transformation of precursor gases, mainly emitted by combustion.
Introduction
Line 38. Check this value (35 µg m-3). WHO 2006 AQG for PM2.5 are 10 µg m-3 as annual average concentration and 25 µg m-3 as 24h mean concentration. WHO 2006 AQG for PM2.5 are 5 µg m-3 as annual average concentration and 15 µg m-3 as 24h mean concentration. Add references.
Lines 44-47. Please, check sentence
Line 58-59. This sentence can be deleted
Lines 66-69. I suggest moving this sentence to Line 54
Line 69. Can you demonstrate it is high quality data? No QA/QC information is presented in section 2. In this paragraph I would indicate that the study is based in high time resolution data.
Data and Methodology
2.1
Line 78. Metals are also inorganic; I would say: “…and 8 soluble components (…”. Same for line 85.
Lines 76-89: IMPORTANT: please, provide some information about blank analysis and QA/QC.
Lines 90-92: were these pollutants measured at the same site where PM2.5?
2.2
Line 109: Do you discard the influence of sea spray? Sea spray contribution can be estimated from Cl- and Na+, using ratios from literature (i.e Lide, D.R., 2005 (http://www.hbepnetbase.com). A major fraction of Na and Cl-, and a fraction of Ca, Mg, SO42- and K can be or marine origin.
2.3: Did you use EPA PMF v5.0 software?
2.5: For the calculation of HQ and LCR, you need to know the average daily exposure concentration (ECinh). For the calculation of ECinh you need to know GA, ET, EF, ED and AT. How do you estimate ET, EF, ED and AT? You refer to two papers but it should be clarified how these parameters were estimated in the text.
Results
3.1
Line 191. What is the time resolution for the average PM2.5 concentrations? Hourly? Daily? Please, indicate it.
Line 193. Seasonal variations are also related to change in emission rates; no only meteorological conditions.
Line 193. Please, delete “in spring” at the end of the line; it is duplicated.
Line 197. Height of the BLH also may influence on increasing PM concentrations in winter.
Line 202: replace “generally affected by vehicles” by “generally related to vehicle emissions”
Line 203: replace “normally affected by stationary sources” by “normally related to stationary sources”
Line 205: please, indicate which seasons correspond to the ratios
Line 206: Ii is not possible to conclude that the contribution of mobile sources if greater than that of stationary sources based in the ratios NO3/SO4. Actually, a significant fraction of NOx can also be emitted by stationary sources.
Line 207: indicate that is % of PM
Lines 209-211: Please, add references.
Caption and first row of Table 2. Delete “Average concentration µg m-3 and component percentage %) from Table and add this information in caption.
Improve caption: Seasonal average concentration of components of PM2.5, in µg m-3 and % in brackets, and meteorological parameters.
Paragraph from Lines 214-230. This paragraph can be improved. Please, try to organize it following the same order for the description of seasons and components.
Line 215: lowest PM2.5 concentration in spring was recorded at 14:00h, not at 17:00h.
Figure 1 caption: Average diurnal variation of the concentrations of major chemical components of PM2.5 per each season.
Lines 233-236: Why did you select these values? A concentration of 75 µg m-3 cannot be considered as clean.
Line 234:” …concentrations were <75…”
Line 235: Figure 2a instead of Figure 3a.
Line 235: Mean of WSIIs? Water soluble inorganics…? Please, write.
Line 236: do you mean ratios or concentrations?
Lines 238-248. It is worthy to explain the variation of the ration NO3/SO4 from spring to winter during the medium and high pollution episodes. IN spring and autumn, concentrations of nitrate are higher than concentration of sulphate during the high pollution episodes. However, in winter sulphate dominates with respect to nitrate. Probably this is related to the influence of coal combustion for heating. Importance of coal combustion in winter is stated in the conclusions but it should be more clearly detailed in the results section.
Lines 247-248: Height of boundary layer can also influence on the accumulation and pollutant favouring reactions.
Line 251: “The differences in different seasons…” can be replaced by “The seasonal differences...”
Line 254: OC is not formed by photochemical reactions. Some particulate organic compounds are formed by photochemical reactions or other transformation processes.
Lines 259-260: Please, explain which were the changes in emissions. This can be also related to the meteorological scenarios favouring accumulation of pollutants.
Figure 2. Quality of Figure can be improved. Caption: please add at the end of caption: “…of the total samples per season”
Lines 265-266. Here you talk about sources and later about Factors. Please, link the number of factor and the sources.
Line 267: explain better the meaning of “other sources”. I would say: Factor 6 wasnot cvleraly assigned to a source, a was attributed to the mis contribution of different sources; then, it was named as “other sources (OS)” (or urban mix UM)
Line 270: Please, explain meaning of %.
Line 274: I would replace “Factor 2 was relevant to CC” by “Given the source profile, Factor 2 was related to Coal combustion emissions”
Line 275: Please, start the sentence indicating that you are now describing Factor 3. “Factor 3 (Figure 3c) was characterized by the association of…”
Lines 278-279: This is not clear; please, rewrite it
Lines 280. Again; please, start naming the Factor you are talking about
Line 280. V and Ni are usually tracers of heavy oil combustion (i.e. shipping emissions; see in ‘t Veld, et al., 2021. Science of the Total Environment, 795, art. no. 148728, DOI: 10.1016/j.scitotenv.2021.148728, and references therein). Please, add references for V and NI as tracers of vehicle emissions.
Line 284: As shown in Figure 33, Factor 5…”
Lines 285-287: Fe, Ti, Mn, K, and Ca (also Al, Si) are tracers of mineral dust (both natural or anthropogenic). K (mainly as K+) is also a tracer of biomass burning.
Figure 3. Caption: please, check it
Paragraph from Lines 292 to 305. Please, carefully revise this paragraph. Do you have any explanation about the biomass burning source identification? Biomass was identified by other works in close areas but it was not identified in this study. Why? Was it due to the species analysed? Is BB included in other sources?
Line 298-299: Which are the local emission characteristics?
Line 299. Delete “CC contributed 22.4%”
Line 303: “in winter” is duplicated; please, delete once.
Table 3. Please add columns for each source identified (you can use the acronyms in the header) and present the % for each one; you don’t need to write the name of source every time. It would be helpful if you present contribution for all sources identified, not only for the 3 main sources,
Figure 4. It can be improved. Enlarge legend. Improve caption: Average annual contribution of the sources identified for PM2.5 in Nanjing in 2018.
Section 3.3.2 and Figures 5 and 6. It is difficult to follow the description and to understand the Figures if you don’t know the location of Provinces and cities mentioned. Can you show them in the maps?
Lines 310-315. There is a clear increase of fugitive dust source during cluster a2 in Spring; what is the origin? can be this related to long range transport of dust? Please, comment in the text.,
Figure 5.- it can be improved. Difficult to see the number in the pies. I suggest decreasing the number figure for %. Caption: “… show the average source contribution…”
Lines 323-324: NH4+ is an important tracer of agricultural activities. Please delete: “As a tracer of the biomass burning source”
Line 3243: replace “Fig 7d” by “Figure 5d”
Line 328: replace “descending” by “ascending” (or by “increasing”)
Lines 338-339. I don’t understand the sentence about attenuation of the impact of long-range transport of industrial pollution by meteorology. This is not shown in Table 2. Please, explain better or deleted it.
Lines 339-342. These 2 sentences can be removed.
3.4. As afore mentioned, how the exposure parameters were estimated should be better explained. Authors refer to other papers, but this should be explained here; were calculated for this or using default values?
Figure 7. Improve caption
Conclusions
Lines 375-377. As aforementioned this was not correctly discussed in the results section.
Data availability: is the PM2.5 composition data available?Citation: https://doi.org/10.5194/egusphere-2023-489-RC2
Yangzhihao Zhan et al.
Yangzhihao Zhan et al.
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