field stringclasses 1
value | paper_idx stringclasses 111
values | doi stringclasses 111
values | type stringclasses 3
values | table_or_image imagewidth (px) 333 2.14k ⌀ | text_or_caption stringlengths 1 115k |
|---|---|---|---|---|---|
atmosphere | 0000 | 10.1016/j.envpol.2018.04.071 | table | Table 1 Summary of the mean concentrations of $\mathrm{PM}_{2.5}$ , OC, and EC $\left(\upmu\mathrm{g}\:\mathsf{m}^{-3}\right)$ in Shenzhen during the controlled and uncontrolled periods at two sampling sites, along with the concentrations of SOA for isoprene, $\mathfrak{x}_{}$ -pinene, $\upbeta.$ -caryophyllene and tol... | |
atmosphere | 0000 | 10.1016/j.envpol.2018.04.071 | image | Fig. 1. Wind rose plots (a) showing the frequency of wind directions in Shenzhen during the controlled period and uncontrolled periods, along with time series of the daily ambient concentrations of $\mathrm{PM}_{2.5}$ at Longgang and Peking University and visibility (b); time series of carbonaceous aerosol (OC, EC, and... | |
atmosphere | 0000 | 10.1016/j.envpol.2018.04.071 | image | Fig. 2. Source apportionment of $\mathrm{PM}_{2.5}\ \mathrm{OC}$ in Shenzhen at Longgang (LG) and Peking University (PU), reported as the average relative source contributions to OC $(\%)$ during controlled and uncontrolled periods. | |
atmosphere | 0000 | 10.1016/j.envpol.2018.04.071 | image | Fig. 3. Ambient concentrations of secondary organic tracers: A) sum of three isoprene SOA tracers, B) the sum of four $\mathfrak{x}$ -pinene SOA tracers, and C) one toluene SOA tracer at LG and PU during the controlled and uncontrolled periods. | |
atmosphere | 0000 | 10.1016/j.envpol.2018.04.071 | image | Fig. 4. Comparison of the fossil and contemporary sources of total carbon (equivalent to the sum of organic and elemental carbon) estimated by a) radiocarbon $(^{14}\mathrm{C})$ analysis, and b) chemical mass balance (CMB) modeling. | |
atmosphere | 0000 | 10.1016/j.envpol.2018.04.071 | text | Not supported with pagination yet | Source apportionment of fine particulate matter organic carbon in Shenzhen, China by chemical mass balance and radiocarbon methods\*
Ibrahim M. Al-Naiema a, Subin Yoon b, Yu-Qin Wang c, d, Yuan-Xun Zhang c, e, Rebecca J. Sheesley b, \*, Elizabeth A. Stone a, f, \*\*
a Department of Chemistry, University of Iowa, Iowa C... |
atmosphere | 0001 | 10.1080/10962247.2012.701193 | image | Figure 1. $\mathrm{PM}_{2.5}$ samples were taken in seven southern China cities: Chongqing (CQ), Guangzhou (GZ), Hong Kong (HK), Hangzhou (HZ), Shanghai (SH), Wuhan (WH), and Xiamen (XM); and seven northern China cities: Beijing (BJ), Changchun (CC), Jinchang (JC), Qingdao (QD), Tianjin (TJ), Xi’an (XA), and Yulin (YL)... | |
atmosphere | 0001 | 10.1080/10962247.2012.701193 | image | Figure 2. Average (square), median (central horizontal bar), 25th and 75th percentiles (lower and upper bars), 1st and 99th percentiles (lower and upper x), and minimum and maximum $(-)$ concentrations for each chemical component across all cities and seasons. Average chemical components are ordered by abundance, with ... | |
atmosphere | 0001 | 10.1080/10962247.2012.701193 | table | Table 1. Arithmetic averages standard deviations (mg m3) for PM2.5 mass and chemical components by city and season. See Figure 1 for city codes. Each average contains 14 values | |
atmosphere | 0001 | 10.1080/10962247.2012.701193 | table | Table 2. Comparison of $\mathrm{PM}_{2.5}$ chemical component ratios for the 14 Chinese cities with ratios from selected cities in Europe, Canada, Mexico, and the United States | |
atmosphere | 0001 | 10.1080/10962247.2012.701193 | image | Figure 3. Relationships between $\mathrm{PM}_{2.5}$ As, $\mathrm{Pb}$ , and $\mathrm{SO}_{4}{}^{2-}$ concentrations from the 14 cities during winter and summer, 2003. | |
atmosphere | 0001 | 10.1080/10962247.2012.701193 | image | Figure 4. Wintertime material balance of $\mathrm{PM}_{2.5}$ for the 14 Chinese cities. Organic matter (OM) is estimated as $1.6\times\mathrm{OC}$ (Chen and Yu, 2007; El-Zanan et al., 2005; ElZanan et al., 2009) to account for unmeasured hydrogen and oxygen. Geological material is estimated as $25\times\mathrm{Fe}$ (Ca... | |
atmosphere | 0001 | 10.1080/10962247.2012.701193 | image | Figure 5. Summertime material balance of $\mathrm{PM}_{2.5}$ for the 14 Chinese cities. Organic matter, geological material, and others are explained in the Figure 4 caption. | |
atmosphere | 0001 | 10.1080/10962247.2012.701193 | table | Table 3. Comparison of PM2.5 and major chemical concentrations (mg m3) from this study with measurements from other PM2.5 studies in Beijing (BJ), Xi’an (XA), Shanghai (SH), and Guangzhou (GZ) | |
atmosphere | 0001 | 10.1080/10962247.2012.701193 | text | Not supported with pagination yet | Journal of the Air & Waste Management Association
Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/uawm20
Winter and Summer $\mathbf{PM}_{2.5}$ Chemical Compositions in Fourteen Chinese Cities
Jun-Ji Cao a , Zhen-Xing Shen b , Judith C. Chow a c , John... |
atmosphere | 0002 | 10.5194/acp-5-3127-2005 | image | Fig. 1. Location of the sampling site at Xi’an, China. | |
atmosphere | 0002 | 10.5194/acp-5-3127-2005 | table | Table 1. Average of OC and EC concentrations during September 2003 to February 2004 at Xi’an, China. | |
atmosphere | 0002 | 10.5194/acp-5-3127-2005 | image | Fig. 2. Time series of $\mathrm{PM}_{2.5}$ mass, organic carbon (OC), elemental carbon (EC), fraction of $\mathrm{PM}_{2.5}$ composed of $\mathrm{OC}\!\times\!1.6\!+\!\mathrm{EC}$ $(\mathrm{TCA}\%)$ , and OC/EC ratios at Xi’an from 13 September 2003 to 29 February 2004. OC is multiplied by 1.6 for the $\mathrm{TCA}\%$ ... | |
atmosphere | 0002 | 10.5194/acp-5-3127-2005 | image | Fig. 3. Relationships between OC and EC concentrations in $\mathrm{PM}_{2.5}$ and $\mathrm{PM_{10}}$ . | |
atmosphere | 0002 | 10.5194/acp-5-3127-2005 | image | Fig. 4. Distribution of $\mathrm{PM}_{2.5}$ and $\mathrm{PM_{10}}$ mass concentrations during fall and winter. The valid paired samples were 17 in fall and 36 in winter. The box plots indicate the mean $24\mathrm{-h}$ concentration and the min, 1st, 25th, 50th, 75th, 99th and max percentiles. A normal curve is fitted t... | |
atmosphere | 0002 | 10.5194/acp-5-3127-2005 | table | Table 2. Statistical summary of the percentage of OC, EC, and $\mathrm{TCA}\%$ in $\mathrm{PM}_{2.5}$ and $\mathrm{PM}_{10}^{\mathrm{a}}$ | |
atmosphere | 0002 | 10.5194/acp-5-3127-2005 | image | Fig. 5. Abundances (mass fraction of total carbon) of eight thermally-derived carbon fractions in ambient and source samples. | |
atmosphere | 0002 | 10.5194/acp-5-3127-2005 | table | Table 3. Comparison of $\operatorname{PM}_{2.5}$ OC, EC at Xi’an with other Asian cities. | |
atmosphere | 0002 | 10.5194/acp-5-3127-2005 | image | Fig. 6. Periodicity of $\mathrm{PM}_{2.5}$ OC, EC, mass, and daily average wind speed. (PSD TISA on the $\mathrm{Y}$ axis refers to Power as Time-Integral Squared Amplitude.) | |
atmosphere | 0002 | 10.5194/acp-5-3127-2005 | table | Table 4. APCA results of fall samples. | |
atmosphere | 0002 | 10.5194/acp-5-3127-2005 | table | Table 5. APCA results of winter samples. | |
atmosphere | 0002 | 10.5194/acp-5-3127-2005 | image | Fig. 7. Relative contributions of major sources to $\mathrm{PM}_{2.5}$ TC during fall and winter 2003. | |
atmosphere | 0002 | 10.5194/acp-5-3127-2005 | text | Not supported with pagination yet | Characterization and source apportionment of atmospheric organic and elemental carbon during fall and winter of 2003 in Xi’an, China
J. J. $\mathbf{Cao}^{1}$ , F. $\mathbf{W}\mathbf{u}^{1,2}$ , J. C. Chow3, S. C. Lee4, Y. Li1, S. W. Chen5, Z. S. $\mathbf{A}\mathbf{n}^{1}$ , K. K. Fung6, J. G. Watson3, C. S. $\mathbf{Zh... |
atmosphere | 0003 | 10.1016/j.scitotenv.2017.01.066 | image | Fig. 1. Sampling site and its surroundings in a rural area in Lingcheng $37^{\circ}21^{\prime}17^{\prime\prime}\mathrm{N}$ , $116^{\circ}28^{\prime}30^{\prime\prime}\mathrm{E}$ ), a district of Dezhou City in Shandong Province, China. | |
atmosphere | 0003 | 10.1016/j.scitotenv.2017.01.066 | image | Fig. 2. CMAQ modeling domains at a horizontal grid resolution of $27\,\mathrm{km}$ over China (D1, with 180 columns and 150 rows, $\sim\!1.97\times10^{7}\,\mathrm{km}^{2})$ and $9\,\mathrm{km}$ over an area in northern China (D2, with 120 columns and 111 rows, $\sim\!1.08\times10^{6}\,\mathrm{km}^{2};$ . The zoom-in ar... | |
atmosphere | 0003 | 10.1016/j.scitotenv.2017.01.066 | table | Table 1 Descriptive statistics of chemical species in $\mathrm{PM}_{2.5}$ in terms of concentrations $(\upmu\mathrm{g}/\uppi^{3})$ and percentages (in brackets, $\%$ ). | |
atmosphere | 0003 | 10.1016/j.scitotenv.2017.01.066 | table | Table 2 Average concentrations of $\mathrm{PM}_{2.5}$ , $S0_{4}^{2-}$ , $\mathrm{NO}_{3}^{-}$ and $\mathrm{NH}_{4}^{+}$ in Lingcheng and other areas in China. | |
atmosphere | 0003 | 10.1016/j.scitotenv.2017.01.066 | table | Table 3 The mass concentration of secondary organic carbon (SOC) during the sampling period. | |
atmosphere | 0003 | 10.1016/j.scitotenv.2017.01.066 | image | Fig. 3. Temporal variations in OC and EC abundances $\left(\upmu\mathrm{g}/\uppi^{3}\right)$ and OC/EC ratios at the sampling site in Lingcheng. | |
atmosphere | 0003 | 10.1016/j.scitotenv.2017.01.066 | table | Table 4 Performance statistics for $\mathrm{PM}_{2.5}$ , OC, EC, $S0_{4}^{2-}$ , $\mathrm{NO}_{3}^{-}$ and $\mathrm{NH}_{4}^{+}$ concentrations. | |
atmosphere | 0003 | 10.1016/j.scitotenv.2017.01.066 | image | Fig. 4. Scatter plots of the daily simulated versus observed concentrations of $\mathrm{PM}_{2.5},$ OC, EC, $S0_{4}^{2-}$ , $\mathrm{NO}_{3}^{-}$ and $\mathrm{NH}_{4}^{+}$ during the winter sampling period in 2010. The daily simulated concentrations were calculated by the averaging the hourly simulated results from the... | |
atmosphere | 0003 | 10.1016/j.scitotenv.2017.01.066 | image | Fig. 5. Comparison between daily simulated and observed $\mathrm{PM}_{2.5}$ , $S0_{4}^{2-}$ , $\mathrm{NO}_{3}^{-}$ , $\mathrm{NH}_{4}^{+}$ , OC and EC at the Lingcheng study site from November 21st to December 20th. Observations are shown with solid line, and simulations are shown with dashed line. The daily simulated... | |
atmosphere | 0003 | 10.1016/j.scitotenv.2017.01.066 | table | Table 5 Average contributions of $\mathrm{PM}_{2.5}$ and main species from local (Lingcheng) and surrounding regions during winter and heavy haze days (in brackets) $(\%)$ . | |
atmosphere | 0003 | 10.1016/j.scitotenv.2017.01.066 | image | Fig. 6. Percent contributions of $\mathrm{PM}_{2.5}$ from the four directions (north, east, west, and south; the simulation area is equally divided into four parts centered on the sampling site). | |
atmosphere | 0003 | 10.1016/j.scitotenv.2017.01.066 | image | Fig. 7. The contribution of $\mathrm{PM}_{2.5}$ per unit area (contribution $/\mathrm{km}^{2}$ ). | |
atmosphere | 0003 | 10.1016/j.scitotenv.2017.01.066 | image | Fig. 8. 12-Hour backward trajectories reaching the sampling site for each hour on 21–24 November and 7, 8, 16, 17, and 21 December on a Lambert conformal projection map of North China. | |
atmosphere | 0003 | 10.1016/j.scitotenv.2017.01.066 | image | Fig. 9. Comparison of the $\mathrm{PM}_{2.5}$ contribution rates during the period of relatively clean days $(\mathrm{PM}_{2.5}\leq75\;\upmu\mathrm{g}/\mathrm{m}^{3})$ , haze days $(75~|\mathrm{{ug/m^{3}}<\mathrm{{PM_{2.5}}<200~|\mathrm{{ug/m^{3}}})}}$ and heavy haze days $(\mathrm{PM}_{2.5}\geq200\,\upmu\mathrm{g}/\ma... | |
atmosphere | 0003 | 10.1016/j.scitotenv.2017.01.066 | text | Not supported with pagination yet | Estimating the contribution of regional transport to $\mathsf{P M}_{2.5}$ air pollution in a rural area on the North China Plain
Dongsheng Chen a,b,⁎, Xiangxue Liu a, Jianlei Lang a,⁎⁎, Ying Zhou a, Lin Wei a, Xiaotong Wang a, Xiurui Guo a
a Key Laboratory of Beijing on Regional Air Pollution Control, Beijing Universit... |
atmosphere | 0004 | 10.1016/j.jes.2015.05.023 | image | Fig. 1 – Temporal variations in (a) air temperature, relative humidity, precipitation, (b) wind speed, wind direction, and (c) $\bf{P M}_{10}$ and $\mathbf{PM}_{2.5}$ mass concentrations and their ratio at the investigated rural site in 2012. | |
atmosphere | 0004 | 10.1016/j.jes.2015.05.023 | table | Table 1 – Atmospheric PM10 and PM2.5 mass concentrations and major chemical components of PM10 at the investigated | |
atmosphere | 0004 | 10.1016/j.jes.2015.05.023 | image | Fig. 2 – Diurnal variations of airborne $\bf{P M}_{10}$ percent concentrations during the crop tillage period in May, the vegetation period from mid-June to mid-September and the harvest period in October at the farm site. | |
atmosphere | 0004 | 10.1016/j.jes.2015.05.023 | image | Fig. 3 – Temporal variations in (a) secondary aerosol-related ions $(\mathbf{NH}_{4}^{+},\mathbf{NO}_{3}^{-}$ and $\mathbf{so}_{4}^{2-})$ , (b) dust-related elements (Al, Ca, Fe and $\mathbf{M}\mathbf{g})$ , (c) carbonaceous species (OC and EC) and (d) biomass burning marker $(\mathbb{K}^{+})$ at the investigated rural... | |
atmosphere | 0004 | 10.1016/j.jes.2015.05.023 | image | Fig. 4 – Temporal variations of the individual contributions of dust (dust), carbonaceous species (carbon), secondary aerosol (SA) and other to the atmospheric $\mathbf{PM_{10}}$ at the rural site and the corresponding average of the four compositions during the tillage period (26 April–15 June), vegetative period (16 ... | |
atmosphere | 0004 | 10.1016/j.jes.2015.05.023 | image | Fig. 5 – Estimated chemical profiles of field tilling-induced and straw burning-induced $\bf{P M}_{10}$ emission. | |
atmosphere | 0004 | 10.1016/j.jes.2015.05.023 | image | Fig. 6 – Diurnal profile of planetary boundary layer (PBL)-adjusted field tilling- and crop burning-induced $\mathbf{PM_{10}}$ emission. | |
atmosphere | 0004 | 10.1016/j.jes.2015.05.023 | text | Not supported with pagination yet | Temporal variability of atmospheric particulate matter and chemical composition during a growing season at an agricultural site in northeastern China
Weiwei Chen1,⁎, Daniel Tong2, Shichun Zhang1, Mo Dan3, Xuelei Zhang1, Hongmei Zhao1
1. Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Chan... |
atmosphere | 0005 | 10.1016/j.scitotenv.2013.12.069 | image | Fig. 1. (a) Sampling location of the Cheng-Yu region (the shaded area) in China. (b) Location of the sampling site (the triangle) in Chengdu. | |
atmosphere | 0005 | 10.1016/j.scitotenv.2013.12.069 | table | Table 1 Measurement parameters and instruments adopted in the sampling site. | |
atmosphere | 0005 | 10.1016/j.scitotenv.2013.12.069 | image | Fig. 2. (a) Times-series of temperature $(\mathrm{T},{}^{\circ}\mathrm{C})$ , dew point $(^{\circ}C)$ , and pressure (P, hPa) during 14–21 May in Chengdu. (b) Times-series of relative humidity $(\mathrm{RH},\%)$ and wind speed $\left(\mathfrak{m}\;\mathbf{s}^{-1}\right)$ ) during 14–21 May in Chengdu. (c) Times-series ... | |
atmosphere | 0005 | 10.1016/j.scitotenv.2013.12.069 | image | Fig. 3. Times-series of $S0_{2}$ , $\mathrm{NO}_{\mathrm{x}}$ $0_{3}$ and CO concentrations $\left(\upmu\mathrm{g}\:\mathfrak{m}^{-3}\right)$ ) during 14–21 May in Chengdu. (Missing data were due to the malfunction of instruments or power failure). | |
atmosphere | 0005 | 10.1016/j.scitotenv.2013.12.069 | image | Fig. 4. (a) Regional distribution of aerosol optical depth (AOD, $550~\mathrm{nm}$ ) retrieved from MODIS during 18–21 May in the Cheng-Yu region. (b) Fire spots retrieved from MODIS on 18 May in Chengdu. (c) Fire spots retrieved from MODIS on 19 May in Chengdu. (Chengdu, Chongqing, Deyang, Ziyang, Meishan, and Dujiang... | |
atmosphere | 0005 | 10.1016/j.scitotenv.2013.12.069 | table | Table 2 Comparison of the average concentrations of $S0_{2}$ $\mathrm{NO}_{\mathrm{x}},0_{3}$ and CO during 14 May to 21 May in Chengdu. | |
atmosphere | 0005 | 10.1016/j.scitotenv.2013.12.069 | image | Fig. 5. Correlation analysis between gaseous pollutants (CO, $S0_{2},$ $\mathrm{NO}_{\mathrm{x}})$ and $\mathrm{PM}_{2.5}$ during the haze episode in Chengdu. | |
atmosphere | 0005 | 10.1016/j.scitotenv.2013.12.069 | image | Fig. 6. The 3-h average mixing height during 14–21 May in Chengdu. | |
atmosphere | 0005 | 10.1016/j.scitotenv.2013.12.069 | image | Fig. 8. Three-day forward matrix trajectories terminated at $12{\cdot}00\ {\sf a.m.}$ (16:00 UTC) for 24-h intervals from 18 May to 21 May (matrix points $30^{\circ}$ , 30.5°, $31^{\circ}\,\mathrm{N}$ by $103^{\circ}$ , 103.5°, $104^{\circ}\mathrm{E}_{\mathrm{,}}$ . | |
atmosphere | 0005 | 10.1016/j.scitotenv.2013.12.069 | table | Table 3 Mass concentrations of $\mathrm{PM}_{10}$ $\mathrm{PM}_{2.5}$ and $\mathrm{PM}_{2.5}$ species in Chengdu. | |
atmosphere | 0005 | 10.1016/j.scitotenv.2013.12.069 | image | Fig. 9. Comparison of the enrichment factors (EFs) during and after the haze episode in Chengdu. | |
atmosphere | 0005 | 10.1016/j.scitotenv.2013.12.069 | text | Not supported with pagination yet | Characteristics and formation mechanism of a heavy air pollution episode caused by biomass burning in Chengdu, Southwest China
Yuan Chen, Shao-dong Xie ⁎
College of Environmental Science and Engineering, Peking University, No. 5 Yiheyuan Rd., Haidian District, Beijing 100871, PR China
H I G H L I G H T S
• Formation ch... |
atmosphere | 0006 | 10.3390/atmos10020078 | image | Figure 1. (a) Location of Sichuan and Chongqing in China; (b) Sampling sites of Chengdu (CD), Neijiang (NJ), and Chongqing (CQ). | |
atmosphere | 0006 | 10.3390/atmos10020078 | table | Table 1. Particle and water-soluble inorganic ion (WSII) concentrations in CD, NJ, and CQ (2012–2013). | |
atmosphere | 0006 | 10.3390/atmos10020078 | image | Figure 2. Seasonal variations of $\mathrm{PM}_{2.5}$ and WSIIs in CD, NJ, and CQ. | |
atmosphere | 0006 | 10.3390/atmos10020078 | image | Figure 3. Scatter plots of total anions vs. total cations in (a) CD, (b) NJ, and (c) CQ. | |
atmosphere | 0006 | 10.3390/atmos10020078 | image | Figure 4. Scatter plots of ammonium and the major acidic anions in $\mathrm{PM}_{2.5}$ of $(\mathbf{a},\mathbf{d},\mathbf{g})$ CD, $({\bf b},{\bf e},{\bf h})\ \mathrm{NJ}.$ , and (c,f,i) CQ. | |
atmosphere | 0006 | 10.3390/atmos10020078 | table | Table 2. The correlation coefficients $(R)$ between $\mathrm{NO}_{3}^{\ensuremath{-}}$ and cations in $\mathrm{PM}_{2.5}$ of CD, NJ, and CQ. | |
atmosphere | 0006 | 10.3390/atmos10020078 | table | Table 3. Seasonal variation of sulfur oxidation ratio (SOR) and nitrogen oxidation ratio (NOR) in CD, NJ, and CQ. | |
atmosphere | 0006 | 10.3390/atmos10020078 | table | Table 4. $\mathrm{NO}_{3}^{\mathrm{~-~}}/\mathrm{SO}_{4}^{\mathrm{~2-~}}$ ratios and NOR/SOR ratios under four different $\mathrm{PM}_{2.5}$ levels. | |
atmosphere | 0006 | 10.3390/atmos10020078 | image | Figure 5. $[\mathrm{NO}_{3}^{\mathrm{~-}}]/[\mathrm{SO}_{4}^{\mathrm{~2-}}]$ ratio as a function of $[\mathrm{NH_{4}}^{+}]/[\mathrm{SO_{4}}^{2-}]$ in (a) CD, (b) NJ, and (c) CQ. | |
atmosphere | 0006 | 10.3390/atmos10020078 | image | Figure 6. $\mathrm{NO}_{3}^{\mathrm{~-~}}$ concentration as a function of excess $\mathrm{NH_{4}}^{+}$ in (a) CD, (b) NJ, and (c) CQ. | |
atmosphere | 0006 | 10.3390/atmos10020078 | image | Figure 7. Relationship between $[\mathrm{NO}_{3}^{\mathrm{~-}}]/[\mathrm{SO}_{4}^{\mathrm{~2-}}]$ and $[\mathrm{NH_{4}}^{+}]/[\mathrm{SO_{4}}^{2-}]$ under different (a) acidity and (b) RH. | |
atmosphere | 0006 | 10.3390/atmos10020078 | table | Table 5. PCA factor loadings of WSIIs in CD, NJ, and CQ. | |
atmosphere | 0006 | 10.3390/atmos10020078 | text | Not supported with pagination yet | Article Characteristics and Sources of Water-Soluble Ions in PM2.5 in the Sichuan Basin, China
Yuan Chen 1, Shao-dong Xie 2,\*, Bin Luo 3 and Chongzhi Zhai 4
School of Safety and Environmental Engineering, Capital University of Economics and Business, NO.121 Zhangjialukou Rd, Fengtai District, Beijing 100070, China; ch... |
atmosphere | 0007 | 10.1016/j.atmosenv.2015.06.054 | table | 3 Table 5 4 Verification statistics of meteorological and chemical simulations during dry and wet seasons. | |
atmosphere | 0007 | 10.1016/j.atmosenv.2015.06.054 | table | 1 Table 7 2 Comparisons of $\mathrm{PM}_{2.5}$ source apportionment results between this study and three studies published before. | |
atmosphere | 0007 | 10.1016/j.atmosenv.2015.06.054 | image | Figure 1 Framework of the source apportionment method used in this study | |
atmosphere | 0007 | 10.1016/j.atmosenv.2015.06.054 | image | Figure 2 Location of $\mathrm{PM}_{2.5}$ sampling site and WRF/Chem modelling domains | |
atmosphere | 0007 | 10.1016/j.atmosenv.2015.06.054 | image | Figure 3 Proportions of seven major components in $\mathrm{PM}_{2.5}$ concentration in dry and wet seasons of 2013 in Guangzhou | |
atmosphere | 0007 | 10.1016/j.atmosenv.2015.06.054 | image | 2013 in Guangzhou | |
atmosphere | 0007 | 10.1016/j.atmosenv.2015.06.054 | image | Figure 5 Analytical results of the 24h air mass back trajectory at $100\mathrm{m}$ elevation during simulated days in wet (a) and dry (b) season, which were run four times per day | |
atmosphere | 0007 | 10.1016/j.atmosenv.2015.06.054 | image | Figure 6 Locations of sizeable industrial and power plants in PRD region | |
atmosphere | 0007 | 10.1016/j.atmosenv.2015.06.054 | text | Not supported with pagination yet | Accepted Manuscript
Source apportionment of $\mathsf{P M}_{2.5}$ in Guangzhou combining observation data analysis and chemical transport model simulation
Hongyang Cui, Weihua Chen, Wei Dai, Huan Liu, Xuemei Wang, Kebin He
PII: S1352-2310(15)30195-3
DOI: 10.1016/j.atmosenv.2015.06.054
Reference: AEA 13932
To appear i... |
atmosphere | 0008 | 10.1016/j.envpol.2018.04.111 | image | Fig. 1. (a) Geography of the Wei valley (cross-sectional view) and (b) locations of the six sampling sites on the topographic map (four urban sites: SS, SF, CA, JK, one urban background site: YL and rural site: CT). Xi'an ${\sim}400\,\mathrm{m}$ a.s.l) lies on the Guanzhong plain, which borders the southern foot of the... | |
atmosphere | 0008 | 10.1016/j.envpol.2018.04.111 | image | Fig. 2. Time series of meteorological parameters (a), concentrations of gas pollutants and PM (b, c, d), sulfur and nitrogen oxidized ratios (the molar ratios of $[S O_{4}^{2-}]$ to $[S O_{4}^{2-}+S O_{2}]$ , $[N O_{3}^{-}]$ to $[N O_{3}^{-}+N O_{2}]$ , respectively) (e), and mass concentrations and fractions of $\math... | |
atmosphere | 0008 | 10.1016/j.envpol.2018.04.111 | image | Fig. 3. Box plots for seasonal variation of crustal material, EC, POC, SOC, sulfate, nitrate, ammonium and trace elements in $\mathrm{PM}_{2.5}$ and $\mathsf{P M}_{10}$ | |
atmosphere | 0008 | 10.1016/j.envpol.2018.04.111 | image | Fig. 4. Time evolution of the concentrations of main species in $\mathrm{PM}_{2.5}$ and the ratio of $\mathrm{NO}_{3}^{-}$ and $S0_{4}^{2-}$ in the winter of 2003 (Cao et al., 2012a), 2006 (Xu et al., 2016), 2008 (Xu et al., 2016), 2010 (Xu et al., 2016) and 2014 (this study). | |
atmosphere | 0008 | 10.1016/j.envpol.2018.04.111 | image | Fig. 5. Annual average mass reconstruction of $\mathrm{PM}_{2.5}$ and $\mathsf{P M}_{10}$ collected from six sites over time. Mass concentrations are labeled outside the pie chart ring. | |
atmosphere | 0008 | 10.1016/j.envpol.2018.04.111 | image | Fig. 6. Average concentrations (bars) and fractions (pies) of each species (crustal material, trace elements, OM, $S0_{4}^{2-}$ $\mathtt{N O}_{3}^{-}$ , $\mathrm{NH_{4}^{+}}$ , EC and others) in $\mathrm{PM}_{2.5}$ and $\mathrm{PM}_{10}$ over six sites are shown as a function of different PM levels. The cyan lines deno... | |
atmosphere | 0008 | 10.1016/j.envpol.2018.04.111 | image | Fig. 7. Scatter plot of daily OC and EC concentrations in PM samples (color bar indicates the daily $0_{\mathrm{x}}\left(\mathrm{NO}_{2}{+}0_{3}\right)$ concentrations). The black line is the upper edge of the whole data and the red line is the regression line of data that used to calculate primary OC/EC. (For interpre... | |
atmosphere | 0008 | 10.1016/j.envpol.2018.04.111 | image | Fig. 8. Scatter plots of SOC vs EC (a), sulfate vs EC (b) for PM in winter. Data were colored by concentrations of arsenic (As). Black lines are the upper and bottom edges of winter data. | |
atmosphere | 0008 | 10.1016/j.envpol.2018.04.111 | image | Fig. 9. Scatter plots of SOC vs $K^{+}$ EC vs $K^{+}$ in the spring, summer, autumn and winter. | |
atmosphere | 0008 | 10.1016/j.envpol.2018.04.111 | text | Not supported with pagination yet | Chemical nature of PM2.5 and $\mathsf{P M}_{10}$ in Xi'an, China: Insights into primary emissions and secondary particle formation
Qili Dai a, Xiaohui Bi a, \*, Baoshuang Liu a, Liwei Li a, 1, Jing Ding a, Wenbin Song b, Shiyang Bi c, Benjamin C. Schulze c, Congbo Song a, Jianhui Wu a, Yufen Zhang a, Yinchang Feng a, P... |
atmosphere | 0009 | 10.1016/j.atmosres.2012.12.004 | image | Fig. 1. Geographical map of the sampling site. | |
atmosphere | 0009 | 10.1016/j.atmosres.2012.12.004 | table | Table 1 Method detection limits, precision, recovery ratio and field blank concentrations of WSIs and PAHs in $\mathrm{PM}_{2.5}$ in the suburb of Shenzhen. | |
atmosphere | 0009 | 10.1016/j.atmosres.2012.12.004 | table | Table 2 Seasonal mean values of meteorological data at the sampling sites. | |
atmosphere | 0009 | 10.1016/j.atmosres.2012.12.004 | image | Fig. 2. Seasonal mean mass concentrations of $\mathrm{PM}_{2.5}$ in the suburb of Shenzhen. | |
atmosphere | 0009 | 10.1016/j.atmosres.2012.12.004 | image | Fig. 3. 72-hour air mass backward trajectories of air mass reaching Shenzhen. |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.