Main Source Areas Research Articles

Transport Influence and Potential Sources of PM2.5 Pollution for Nanjing

In this study, 24-hour backward trajectories of the air mass in Nanjing were calculated by using the HYSPLIT model with the NCEP global reanalysis data from March 2019 to February 2020. The backward trajectories combined with the hourly concentration data of PM2.5 were then utilized in the trajectory clustering analysis and potential pollution source analysis. The results showed that the average concentration of PM2.5 in Nanjing was(36±20) μg·m-3 during the study period, with 17 days exceeding the grade Ⅱ national ambient air quality standards (75 μg·m-3). PM2.5 concentration exhibited clear seasonal variation, with winter (49 μg·m-3)>spring (42 μg·m-3)>autumn (31 μg·m-3)>summer (24 μg·m-3). PM2.5 concentration was significantly positively correlated with surface air pressure but significantly negatively correlated with air temperature, relative humidity, precipitation, and wind speed. Based on the trajectories, seven transport routes were identified in spring, and six routes for the other seasons. The northwest and south-southeast routes in spring, southeast route in autumn, and southwest route in winter were the main pollution transport routes in each season, with the characteristics of short transport distance and slow air mass movement, indicating that local accumulation was one of the main reasons for the high value of PM2.5 in quiet and stable weather. The distance of the northwest route in winter was large, and the PM2.5 concentration was 58 μg·m-3, which was the 2nd highest concentration in all routes, indicating that the cities in the northeast of Anhui had a great transport influence on Nanjing PM2.5. The distribution of PSCF and CWT was relatively consistent, and the main potential source areas were mainly local and adjacent areas of Nanjing, indicating that PM2.5 control is needed to strengthen local control and carry out joint prevention and control with adjacent areas. Winter was most affected by transport, its main potential source area was located at the junction of northwest Nanjing and Chuzhou, and the main source origin was in Chuzhou; therefore joint prevention and control should be expanded to Anhui.

Influence of Typhoon Nangka Process on Ozone Pollution in Hainan Island

In order to explore the influence of the 2016 typhoon Nangka on ozone (O3) concentration in Hainan Island, this study employed correlation analysis and backward trajectory simulated methods, using the hourly air quality monitoring data, meteorological data, EAR5 reanalysis data, and bright temperature (TBB) infrared from the Himawari-8 satellite from October 10 to 14, 2020. The results showed that, during the typhoon process from October 11 to 13, the O3-8h (maximum of 8 hours sliding average) concentration exceeded the standard. The averaged ρ(O3-8h) of Hainan Island reached its peak value (130.5 μg·m-3) in October 12, 2020, with the O3-8h concentration exceeding the standard in four cities and counties, in which Lingao County reached the highest concentration of 198.44 μg·m-3. During the typhoon process, the hourly O3 concentration was negatively correlated with precipitation, relative humidity, and wind speed and positively correlated with air pressure and air temperature. Moreover, the correlation coefficients between O3 with precipitation, air pressure, and relative humidity exceeded the 99.9% confidence level. The southeastern coastal provinces of China were the main contribution source area for this ozone pollution process on Hainan Island. Affected by the downdraft inside the western Pacific subtropical high (WPSH) and the downdraft outside the circumference of typhoon Nangka, vertical transport in the atmosphere appeared over the contribution source area. The meteorological conditions were favorable for atmospheric photochemical reactions. Air pollutants were transported to Hainan Island along the northeast airflow around the typhoon, resulting in the occurrence of an O3 pollution event. In addition, this study built a weather conceptual model of O3 pollution in Hainan Island affected by typhoon Nangka, which can be used as a reference for the joint pollution prevention and control by air pollution prediction, early warning, and environmental management departments.

Paleogene evolution of the External Rif Zone (Morocco) and comparison with other western Tethyan margins

The Paleogene evolution of the NW margin of the African Plate (Western External Rif Zone) was studied by means of multidisciplinary analyses of twenty-one stratigraphic logs, including tectofacies recognition, petro-mineralogical results, and thicknesses analysis. Four stratigraphic intervals were recognized separated by three unconformities coarsely aligned with the Cretaceous–Paleogene, Eocene–Oligocene and Oligocene–Miocene boundaries, respectively. Tectofacies appear from the late Ypresian being more frequents from the Oligocene as the tectonic activity increases. The petrology of detrital suites indicates recycled orogen-derived sediments, with quartz supplied from metamorphic rocks of the Atlas orogen and/or the African craton. On the basis of Mesozoic clay mineral assemblages reported in the literature, the clay mineralogy of mudstones suggests upper Jurassic to upper Cretaceous terrains from the Internal Intrarif as the main source area of the Paleocene–Eocene successions, with sediment provenance reversion during the Oligocene and additional contribution of Paleocene to lower Eocene suites. The different displacement capability of the identified aluminic-magnesic clay mineralogy enabled to deduce the relative proximity of the source area. These findings point out a complex sedimentary evolution characterized by a mixture of different lithotypes dating back to upper Jurassic. X-ray parameters helped to identify evidences of synsedimentary tectonics overprinting the inherited mineralogy during some periods with weak burial diagenesis at most. During the Paleogene a foreland basin is formed mainly in the Mesorif and Prerif sub-domains. This foredeep was represented by two ‘sub-geosynclines’ separated by a relative bulge located in the External Mesorif. The Internal Intrarif could represent the relative orogenic front, advancing on the External Intrarif. The Eocene forebulge was located in the Ridges Domain, while the Gharb Basin was the backbulge of the system. During the Oligocene the depocentral area migrated southward and a homogeneization of thicknesses took also place in the whole margin. In this new configuration, the foredeep would be located in the External Mesorif (previously a relative bulge) while the Ridges Domain and the Gharb Basin continued to act as the system forebulge and backbulge, respectively. A comparison with the Paleogene evolution of other western Tethys external margins (Betic Chain, Tunisian Tell, Sicilian Maghrebids, and Apennines) has revealed more similarities than differences. The effects of the Eo-Alpine tectonics are recognized everywhere even if they decrease both from N to S, and from W to E in the different considered margins. The evolution of the compared margins shows a common pre-foredeed (Paleocene-Eocene) and beginning of foredeep (Oligocene) stages in the foreland basins.

Long-distance transport of clastic material revealed by monazite and muscovite dating: Albian arenites, extra-Carpathian Poland

The absolute ages based on chemical UPb dating of monazite (CHIME) and 40Ar/39Ar muscovite were used for provenance determination of the Albian arenites of the southern part of the extra-Carpathian Poland. The ages of detrital monazites allowed a division of the study area into two domains: western and eastern, related to the Miechów and Lublin areas respectively. The western domain is characterized by a unimodal distribution of monazite ages – 330–380 Ma that unequivocally indicates a Variscan provenance of the detrital monazite. The muscovite 40Ar/39Ar method applied to a western domain sample yielded a primary 360.0 ± 1.21 Ma age, confirming a Variscan source of the detrital material. The eastern domain is characterized by a polymodal distribution of monazite ages and is further divided into two subdomains: northeastern and southeastern. Both subdomains are characterized by a polymodal distribution of monazite ages peaking at 390–490 Ma; 0.8–1.1 Ga; ca. 1.5 Ga and ca. 1.8 Ga, indicating the Caledonian, Sveconorwegian, Hallandian-Danopolonian plus Gothian and Svecofennian origins of the detrital monazite. The southeastern subdomain additionally has a significant amount of detrital monazite with 330–380 Ma ages, suggesting a notable influence of a Variscan source. The 40Ar/39Ar muscovite data from the northeastern subdomain sample, ca. 476.4 ± 1.27 and subordinate 496.4 ± 2.83 Ma, confirms that a Caledonian source area was active during sedimentation of the Albian deposits. Detrital muscovite from southeastern subdomain sample yielded two ages: 478.1 ± 3.71 Ma and 502.1 ± 0.65 Ma also indicating a Caledonian age of the detrital muscovite. The monazite and muscovite data indicate at least two independent main ultimate source areas: the Bohemian Massif for the Miechów area (western domain) and the Baltic Shield for the Lublin area (eastern domain). The results document an over 1200 km long transport of clastic material in the Central European Sedimentary Basin during the Albian.

Chemical characterization of marine aerosols from two cruises over the South China Sea: Importance of biomass burning and secondary formation

Total suspended particle (TSP) samples were collected during June–July 2015 in the northern South China Sea (NSCS) and August–September 2016 in the western South China Sea (WSCS). Water-soluble ions (WSIs), organic carbon (OC), elemental carbon (EC), and organic compounds were measured. The average concentrations of WSIs, OC, EC and organic compounds were 19.4 ± 10.9 μg m−3, 2.48 ± 1.54 μgC m−3, 0.31 ± 0.25 μgC m−3 and 789 ± 217 ng m−3 in the NSCS, and were 10.2 ± 4.71 μg m−3, 1.76 ± 1.82 μgC m−3, 0.43 ± 0.32 μgC m−3 and 781 ± 342 ng m−3 in the WSCS. In both cruises, sea salt ions (Na+ and Cl−) and secondary inorganic ions (SO42−, NO3−, and NH4+) were the main species of WSIs, accounting for 54.0 % and 43.6 % in the NSCS, and for 35.0 % and 54.0 % in the WSCS. The secondary products (dicarboxylic acids and aromatic acids) (NSCS: 73.3 %; WSCS: 73.9 %) and saccharides (NSCS: 19.0 %; WSCS: 18.0 %) accounted large fractions of organic compounds in aerosol particles over the SCS. These results suggest sea salt emissions and secondary formation are the main sources of the aerosols over the SCS in summer. The positive correlations between the biomass burning tracers (nss-K+ and levoglucosan) and OC as well as organic compounds indicated that biomass burning from nearby continents was also an important source of organic aerosols over the SCS. Based on back-trajectory analysis and satellite fire spots, Indochina Peninsula and China were proposed as the main continental source areas of non-sea salt WSIs and organic compounds. Our results highlight the significant contribution of continental outflow especially biomass burning and photochemical secondary oxidation to the organic compositions of aerosol particles over the SCS in summertime.

Source attribution of particulate matter in Berlin

The exposure to ambient particulate matter in metropolitan areas is a major health problem. A prerequisite for formulating effective mitigation strategies it to understand the origin of particulate matter in terms of source regions and sectors. We performed a source attribution of particulate matter (PM) for the Berlin agglomeration area covering the period from 2016 to 2018 using the LOTOS-EUROS chemistry transport model. The (3 year-) mean modelled urban background PM2.5 concentration (10.4 μg/m³) is largely explained by households (3.2 μg/m³) and industry & energy (2.0 μg/m³), while the remaining source sectors contribute the other half. The modelled annual mean urban increment for PM2.5 is mainly attributed to households (1.6 μg/m³) and traffic (0.5 μg/m³). With respect to its relative shares the PM10 source attribution looks similar to that of PM2.5 throughout the year, but with enhanced natural contributions. From a geographical perspective the main source area for the PM2.5 in Berlin is Germany (5.1 μg/m³) itself, followed by the contributions from transboundary transport (3.4 μg/m³). The German sources could be further split into Berlin (2.6 μg/m³), Brandenburg (0.7 μg/m³) and remaining states of Germany (1.8 μg/m³). About one third of the foreign shares can be attributed to Germany's neighbouring countries Poland and Czech Republic. During episodes these contributions can significantly differ, e.g. in February 2017 the Polish contribution is about 1/3rd. The sectoral contributions agree with previous findings except that our study indicates lower contributions for traffic. The model's underestimation of total PM is largely caused by an underestimation of the coarse mode PM. Both the coarse mode urban increment as well as the regional background concentrations are underestimated by the model, especially during summer. We suggest that the enhanced coarse material (in the city) during warm seasons is predominated by (road) resuspension processes which need more of our attention to further improve our models.

PSCF and CWT methods as a tool to identify potential sources of 7Be and 210Pb aerosols in Granada, Spain

This research is focused on studying the preferred source regions and the pathways of the air masses with high particulate concentrations impacting on the activity concentrations of 7Be and 210Pb aerosols in Granada atmosphere. For this purpose, three different source-receptor methods have been used: Cluster Analysis, Potential Source Contribution Function (PSCF), and Concentration Weighted Trajectory (CWT). Air filter samples were weekly collected and analysed in Granada university (Spain 37.177N, 3.598 W, 687m a.s.l.) during 12 years (2006–2017) for the activity concentration of 7Be, and during 5 years (2010–2014) for the one of 210Pb. The time series of the collected data indicate that the concentration of both radiotracers present a cyclical and seasonal pattern, in association with their origins and atmospheric conditions. Clustering analysis showed that the air masses arriving to Granada can be classified as: (1) tropical continental air masses coming from the Mediterranean Sea, (2) tropical and warm polar maritime air masses produced over the Atlantic Ocean, and (3) continental air masses originated over Europe and Northern Africa. The PSCF and CWT methods confirmed that the main source areas of 7Be are located in the Atlantic coast of southern Morocco, and Northern Africa. On the other hand, southern France and the Algerian desert were found to be the main region sources of 210Pb. In addition, the Mediterranean Basin has been postulated as a strong source region for 7Be and 210Pb. Furthermore, the PSCF and CWT models show that the regions with larger 7Be/210Pb ratios are located in the Atlantic Ocean, due to frequent stratospheric intrusions specially during the winter months.

Analysis of PM2.5 Transmission Characteristics in Main Cities of Jinzhong Basin in Winter

In this study, we analyzed the hourly concentration data of PM10 and PM2.5 in major cities in Jinzhong basin from 2017 to 2019. The main distribution characteristics of aerosols in Jinzhong and Taiyuan were determined, and PM2.5 hourly concentration data and HYSPLIT in Jinzhong basin in winter were discussed. The results showed that the overall level of particulate matter concentration in Taiyuan was higher than that in Jinzhong, and the monthly and seasonal variation characteristics were similar. All showed high concentrations in winter and low concentrations in summer, and the highest concentration value appeared in January. The aerosol pollution caused by the static and stable weather in Jinzhong was more common than that caused by the sand and dust weather in Taiyuan. The distribution of particulate matter showed the characteristics of more intermediate values in Jinzhong and more high and fewer low values in Taiyuan, and winter was the highest incidence season of PM2.5 pollution in Jinzhong basin. PM2.5 transmission passageways in the main cities of Jinzhong basin in winter could be divided into four categories:class 1 was transmitted along the transverse valley of Taihang Mountain, and class 2 was the southeast transmission channel. Class 1 and class 2 were the short-range transmission passageways; air masses carried more moisture, and PM2.5 transmitted along such passageways allowed moisture to be absorbed more easily, increasing levels and aggravating local pollution. Class 3 was the northwest passageway, corresponding to the most serious pollution period of PM2.5 in Jinzhong basin before the arrival of cold air, which also corresponded to the dust transmission passageway. Class 4 was the Fenwei Plain passageway, corresponding to high-concentration PM2.5 pollution. Areas with dense pollution tracks (more than 100 pollution tracks) and areas with slow air flow movement (RTA pollution track end points greater than 50) easily became potential source areas of target cities (PSCF contribution greater than 0.7). The main potential source areas of PM2.5 in winter in Jinzhong (PSCF contributing more than 0.7) were mainly distributed in Linfen, Jincheng, and other places in Shanxi province, as well as in the north of Henan province, the south of Hebei province, and central and south Shaanxi province. The distribution range of main potential source areas of PM2.5 in Taiyuan in winter was wider than that in Jinzhong, including the south of Lvliang, Yangquan, Linfen, and Yuncheng and the south of Jinzhong in Shanxi, as well as most areas in southern Shaanxi, northern Henan province, and southern Hebei province. In addition, the PSCF distribution of high-value centers above 0.9 was wider than that of Jinzhong. When pollution occurs in cities that PSCF contributed more than 0.9, special attention should be paid to the influence of mutual transmission between them and cities in Jinzhong basin. Jinzhong and Taiyuan showed different distribution characteristics corresponding to the surface wind direction when light and higher pollution occur, when the wind direction near the ground in Jinzhong was E, the frequency of light and higher pollution was 8.1%; it was the highest in all wind directions. When the wind direction near the ground in Taiyuan was SSW, the frequency of light to higher polluted weather was the highest in all wind directions (5.1%). In the case of calm wind, the frequency of light to higher pollution in Taiyuan (3.4%) was higher than that in Jinzhong (0.5%).

Characteristics and Source Analysis of Water-soluble Inorganic Pollution in PM2.5 During Summer in Central China

In order to investigate the pollution characteristics and sources of water-soluble ions in atmospheric PM2.5 in different regions of central China during summer, Wuhan, Suizhou, and Pingdingshan were selected as urban, suburban, and rural monitoring stations, respectively, to collect PM2.5 samples, and the mass concentration of PM2.5 in the atmosphere and the contents of eight water-soluble ions were analyzed. The results showed that ρ(water-soluble ions) at the three sites showed obvious spatial distribution characteristics, with Pingdingshan[(36.29±9.82) μg·m-3] > Wuhan[(32.55±10.05) μg·m-3] > Suizhou[(26.10±6.23) μg·m-3], accounting for 52.47%, 51.32%, and 48.61% of the PM2.5 mass concentration, respectively. In the Pingdingshan station, the proportion of water-soluble ions was the largest due to biomass combustion in the rural area. Additionally, SNA (SO42-, NO3-, and NH4+) were the main ionic components, accounting for 95.65%, 96.12%, and 97.33% of the total water-soluble ions, respectively. The mean values of SOR of the Wuhan (0.64) and Suizhou (0.63) stations were higher than that of the Pingdingshan station (0.50), whereas the NOR values of the Wuhan (0.18) and Pingdingshan (0.19) stations were higher than that of the Suizhou station (0.15). The difference in SOR and NOR among stations was affected by the secondary conversion mechanism, the ammonia-rich environment, and the surrounding traffic sources, respectively. The PM2.5 at the Wuhan and Pingdingshan stations was in general alkaline, whereas at the Suizhou station it was neutral or weakly acidic, which was mainly caused by differences in NH4+. NH4+ mainly existed in the form of (NH4)2SO4 and NH4NO3 at the Wuhan and Pingdingshan stations, whereas at the Suizhou station it mainly existed in the form of (NH4)2SO4 or (NH4)HSO4. PCA-MLR analysis revealed that the Wuhan (89.27%) and Suizhou (67.38%) stations were the most affected by secondary conversion sources, whereas the Wuhan station was also affected by industrial sources (8.54%) and coal sources (2.27%). The pollution sources of the Suizhou station also included biomass combustion (24.42%) and dust sources (8.25%). The Pingdingshan station was most affected by biomass combustion (58.37%), followed by dust and combustion sources (38.05%) and traffic sources (3.58%). The analysis of potential sources of SNA (PSCF) showed that the main potential source areas of Wuhan were the boundary of Hubei, Henan, and Anhui and the southwest area of Anhui. Suizhou and Pingdingshan were affected by long-distance transport, and the main potential source regions were distributed in Shanghai, Jiangsu, and Anhui provinces from the east coast to the west.

Spatiotemporal Distribution and Seasonal Characteristics of Regional Transport of PM2.5 in Yuncheng City

The spatiotemporal distribution characteristics of PM2.5 pollution in Yuncheng City were analyzed based on the ambient air quality monitoring data from March 2019 to February 2020, and the hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) and cluster analysis were used to discuss the contamination transportation pathway and the distribution of potential pollution sources affecting PM2.5 in Yuncheng City in different seasons. The results showed that the PM2.5 concentration in Yuncheng was the highest in winter (111.24 μg·m-3) and the lowest in summer (30.02 μg·m-3). PM2.5/PM10 was greater than 0.6 in autumn and winter, indicating that the particulate matter pollution in Yuncheng City in autumn and winter was mainly fine particulate matter; spatially, the annual mean value of PM2.5 presented distribution characteristics that were high in the northern and central regions and low in the eastern and western regions. The high-value areas of PM2.5 were significantly and strongly correlated with SO2, NO2, and CO, indicating that local emissions contributed to the high values. The highest values in spring and winter were located in Hejin City (58.50 μg·m-3) and Jishan County (142.33 μg·m-3), and the highest values in summer and autumn were located in Pinglu County (36.92 μg·m-3) and the Salt Lake area (62.94 μg·m-3), respectively. Transportation analysis showed that spring and winter were mainly affected by air masses transporting northwestward, accounting for 58.69% and 55.77%. In summer, air masses were mainly eastward and southward, and in autumn, pollution was from short-distance transport air masses from southwestern Henan. The largest ratio was 32.89%; the potential source area was the smallest in spring and summer; it then began to grow in autumn, and it was the widest in the winter and had the highest contribution. The main source area in spring and summer was located in western and central Henan, and in autumn and winter, source areas were concentrated at the junction of Shaanxi, Shanxi, and Henan and west of Shaanxi.

Temporal and Spatial Analysis of PM2.5 and O3 Pollution Characteristics and Transmission in Central Liaoning Urban Agglomeration from 2015 to 2020

The central Liaoning urban agglomeration is an important heavy industry development base in China, and also an important part of the economy in northeast China. The atmospheric environmental problems caused by the development of heavy industry are particularly prominent. Trajectory clustering, potential source contribution (PSCF), and concentration weighted trajectory (CWT) analysis are used to discuss the temporal and spatial pollution characteristics of PM2.5 and ozone concentrations and reveal the regional atmospheric transmission pattern in central Liaoning urban agglomeration from 2015 to 2020. The results show that: (1) PM2.5 in the central Liaoning urban agglomeration showed a decreasing trend from 2015 to 2020. The concentration of PM2.5 is the lowest in 2018. Except for Benxi (34.7 µg/m3), the concentrations of PM2.5 in other cities do not meet the standard in 2020. The ozone concentration in Anshan, Liaoyang, and Shenyang reached the peaks in 2017, which are 68.76 µg/m3, 66.27 µg/m3, and 63.46 µg/m3 respectively. PM2.5 pollution is the highest in winter and the lowest in summer. The daily variation distribution of PM2.5 concentration showed a bimodal pattern. Ozone pollution is the most serious in summer, with the concentration of ozone reaching 131.14 µg/m3 in Shenyang. Fushun is affected by Shenyang intercity pollution, and the ozone concentration is high. (2) In terms of spatial distribution, the high values of PM2.5 are concentrated in monitoring stations in urban areas. On the contrary, the concentration of ozone in suburban stations is higher. The high concentration of ozone in the northeast of Anshan, Liaoyang, Shenyang to Tieling, and Fushun extended in a band distribution. (3) Through cluster analysis, it is found that PM2.5 and ozone in Shenyang are mainly affected by short-distance transport airflow. In winter, the weighted PSCF high-value area of PM2.5 presents as a potential contribution source zone of the northeast trend with wide coverage, in which the contribution value of the weighted CWT in the middle of Heilongjiang is the highest. The main potential source areas of ozone mass concentration in spring and summer are coastal cities and the Bohai Sea and the Yellow Sea. We conclude that the regional transmission of pollutants is an important factor of pollution, so we should pay attention to the supply of industrial sources and marine sources of marine pollution in the surrounding areas of cities, and strengthen the joint prevention and control of air pollution among regions. The research results of this article provide a useful reference for the central Liaoning urban agglomeration to improve air quality.

Study on Transmission Channel and Pollution Sources Region of O3 in Qingyuan City.

Based on the Lagrange mixed single-particle trajectory model and NCEP global reanalysis meteorological data, the 72 h backward airflow trajectory in Qingyuan City in different seasons from 2018 to 2020 was analyzed by cluster analysis. Combined with the hourly average concentration data of O3, the potential source contribution factor (PSCF) analysis and concentration weighted trajectory (CWT) analysis were used to study the regional transport and possible source area of O3 in Qingyuan City and analyzed the relationship among O3 and wind speed, wind direction, NO2, and CO. The results showed that from 2018 to 2020, the most significant proportion of primary pollutants in Qingyuan City was ozone. The annual average concentration reached the highest value since monitoring in 2019. In 2020, the impact of epidemic prevention and control decreased. The daily average concentration change characteristics showed a single peak, with the highest concentration in the afternoon, the highest peak concentration in summer, followed by spring, and the lowest concentration in winter. There are differences in the concentration of O3 between different sources of airflow in Qingyuan City. The potential source contribution factor shows that the high-value covered areas are mainly in Guangzhou, Foshan, and Zhongshan, which can be considered the main potential source areas. These areas can be regarded as the main potential source areas. The concentration weight trajectory showed that external and local sources affected the O3 pollution in Qingyuan during the four seasons. The high ozone concentration in Qingyuan mainly appeared in the south wind direction, indicating that the high ozone concentration in Qingyuan was greatly affected by the external transmission of the southern Pearl River Delta. The correlation between ozone concentration and CO concentration is poor, and the effect on ozone concentration is less than that of NO2.

The Provenance and Tectonic Settings of the Greywacke Member of the Late Neoproterozoic Hazara Formation Lesser Himalayas, Northern Pakistan: Evidence from Geochemistry and Petrography

The petrographic and geochemical analysis of the greywacke horizon of the late Neoproterozoic Hazara Formation from the Hazara Mountains has been investigated to determine the provenance, tectonic settings and weathering history of the sediments. The Late Neoproterozoic Hazara Formation is a thick sedimentary sequence comprising of greywacke, shale, argillites, siltstone, and limestone. The greywackes are characterized by fine to medium-grained, moderately sorted and sub-angular to sub-rounded framework grains. They are rich in quartz, lithic fragments and clay minerals. The petrographic investigation of the greywackes categorized them as feldspathic greywacke in the QFR diagram. The quartz content is higher in sandstone and may reach to 70%, which indicates a weathered felsic source. Chemical Index of Alteration values of greywacke suggests that the source region has experienced highly weathering conditions with a warm and moist climate. Various geochemical interpretations, elemental ratios like Th/Sc, La/Sc,Th/Cr, and positive Eu anomalies indicate that the greywackes of the Hazara formation derived from a felsic source and were deposited within an active continental margin tectonic settings. The main source area of the sediments of the greywackes was located to south to southeast, which may possibly be the Aravali orogeny, central Indian craton and Bundelkhand craton. Finally, the geochemical data of the major elements point to a felsic igneous provenance for the greywacke.

Review on Lagrangian Particle Tracking Modeling for Floating Objects around the Korean Peninsula

Marine debris is becoming an increasingly serious problem. Using a Lagrangian particle model one can calculate the trajectories of various floating objects including marine debris. We reviewed Lagrangian particle tracking of floating objects in the seas around Korea from three recent studies. The first one was on the fate of marine debris from lands through the rivers discharging into the seas around the Korean Peninsula. The main path of the debris depended on their geographical locations. The debris from the rivers on the east coast of China moved southward along the Chinese coast, to the Korea Strait, or to the North Pacific Ocean via the Kuroshio Current (KC). That from the rivers located on the west coast of the Korean Peninsula moved southward to reach the KC, and then to the North Pacific Ocean. The main pathway of the debris from the Nakdong Rivers was toward the East Sea (ES). The particles released from the Tumen River were limited to the ES. In the second example, the pathways of the debris released through the Tumen River located between the North Korea and Russia during the flooding induced by the typhoon Lionrock in August 2016 were investigated. The debris was transported southward along the east coast of the Korean Peninsula by the southward North Korea Cold Current while affected by the wind. Three potential hotspots of debris accumulation along the coast were also found. In the third example, the most probable route of a wave buoy found at Cape Mendocino, California, USA was deduced. The buoy moved from Jeju Island toward Taiwan, and then to the North Pacific via the KC. These model results would help us to establish efficient cleaning and management plans of marine debris by showing us the main accumulation sites, pathways and source areas.

Regional Air Pollutant Characteristics and Health Risk Assessment of Large Cities in Northeast China

This study systematically investigated the pollution characteristics of atmospheric O3 and PM2.5, regional transport, and their health risks in three provincial capitals in northeast China during 2016–2020. The results show that O3 concentrations showed a trend of high summer and low winter, while PM2.5 concentrations showed a trend of high winter and low summer during these five years. The results of the correlation analysis indicate that external sources contribute more O3, while PM2.5 is more from local sources. The backward trajectory clustering analysis results showed that Changchun had the highest share of northwest trajectory with a five-year average value of 67.89%, and the city with the highest percentage of southwest trajectory was Shenyang with a five-year average value of 23.95%. The backward trajectory clustering analysis results showed that the share of the northwest trajectory decreased and the share of the southwest trajectory increased for all three cities in 2020 compared to 2016. The results of the potential source contribution function (PSCF) and concentration weighting trajectory (CWT) analysis showed that the main potential source areas and high concentration contribution areas for PM2.5 in the northeast were concentrated in Mongolia, Inner Mongolia, Shandong Province, and the northeast, and for O3 were mainly located in Shandong, Anhui, and Jiangsu Provinces, and the Yellow Sea and Bohai Sea. The non-carcinogenic risk of PM2.5 in Harbin was high with a HQ of 2.04, while the other cities were at acceptable levels (HQ < 0.69) and the non-carcinogenic risk of O3 was acceptable in all three cities (HQ < 0.22). However, PM2.5 had a high carcinogenic risk (4 × 10−4 < CR < 0.44) and further treatment is needed to reduce the risk.

The Maz Metasedimentary Series (Western Sierras Pampeanas, Argentina). A relict basin of the Columbia supercontinent?

AbstractThe Maz Metasedimentary Series is part of the Maz Complex that crops out in the sierras of Maz and Espinal (Western Sierras Pampeanas) and in the Sierra de Umango (Andean Frontal Cordillera), northwestern Argentina. The Maz Complex is found within a thrust stack of Silurian age, which later underwent open folding. The Maz Metasedimentary Series mainly consists of medium-grade garnet–staurolite–kyanite–sillimanite schists and quartzites, with minor amounts of marble and calc-silicate rocks. Transposed metadacite dykes have been recognized along with amphibolites, metagabbros, metadiorites and orthogneisses. Schist, quartzite and metadacite samples were analysed for SHRIMP U–Pb zircon dating. The Maz Metasedimentary Series is polymetamorphic and records probably three metamorphic events during the Grenvillian orogeny, at c. 1235, 1155 and 1035 Ma, and a younger metamorphism at c. 440–420 Ma resulting from reactivation during the Famatinian orogeny. The sedimentary protoliths were deposited between 1.86 and 1.33–1.26 Ga (the age of the Andean-type Grenvillian magmatism recorded in the Maz Complex), and probably before 1.75 Ga. The main source areas correspond to Palaeoproterozoic and, to a lesser magnitude, Meso-Neoarchaean rocks. The probable depositional age and the detrital zircon age pattern suggest that the Maz Metasedimentary Series was laid down in a basin of the Columbia supercontinent, mainly accreted between 2.1 and 1.8 Ga. The sedimentary sources were diverse, and we hypothesize that deposition took place before Columbia broke up. The Rio Apa block, and the Río de la Plata, Amazonia and proto-Kalahari cratons, which have nearby locations in the palaeogeographic reconstructions, were probably the main blocks that supplied sediments to this basin.

Cenozoic Tectono‐Geomorphologic Evolution of the Pamir‐Tian Shan Convergence Zone: Evidence From Detrital Zircon U‐Pb Provenance Analyses

AbstractThe Pamir is the northwestward continuation of the Tibet‐Himalaya orogen and translated ∼50–300 km northward toward the Tian Shan in Mesozoic‐Cenozoic times. Although this region has been studied extensively over the past few decades, our knowledge of the timing of mountain building in the Pamir is incomplete. In this study, we applied provenance analyses of Cretaceous‐Pliocene sediments from the Tierekesazi section in the Pamir‐Tian Shan corridor to reconstruct the Cenozoic evolution of the Pamir‐Tian Shan orogens. Provenance data from new detrital zircon U‐Pb ages and paleocurrent measurements indicate that the main source area of sediments in the studied section shifted from the Tian Shan to the Northern Pamir at ∼41–40 Ma. When combined with published provenance data, eastward decreasing sediment transport distances suggest that the Pamir was characterized by an asymmetric drainage system with larger drainage basins developed in the western Pamir than the eastern Pamir since the late Eocene. This resulted from either eastward decrease in precipitation rate caused by the uplift of the Pamir orocline or relatively low topography of the western Pamir. Furthermore, observed east and south directed paleocurrents and a dominance of Paleozoic detrital zircon U‐Pb ages in the upper Miocene‐Pliocene sediments suggest the SW Tian Shan was uplifted and became the primary provenance of the Tierekesazi section in the late Miocene. Simultaneously, the thrust belt of the Pamir propagated into its northern foreland and the present‐day east flowing drainage system in the eastern Pamir‐Tian Shan convergence zone was established in the late Miocene.

Influence of Pollutant Transport from Both Sides of the Taihang Mountains on Cross-Valley Urban Aerosols

Based on hourly concentration data of PM10 and PM2.5 from 2017 to 2019 and wind speed and direction data at the corresponding times in Yangquan, an urban valley of the Taihang Mountains, the characteristics of air transport in a cross-valley urban area and their influence on aerosols in Yangquan were analyzed using the HYSPLIT model, cluster analysis, and the potential source contribution factor and concentration weight trajectory methods. The pollutant transport characteristics on the east and west sides of the Taihang Mountains were evaluated. The diurnal variation of the aerosols showed a single peak and single valley, with continuous improvements in aerosol concentration from evening to the morning of the next day. The maximum aerosol concentration occurs at 10:00-11:00 in winter and at 09:00 in other seasons, whereas the minimum value occurs at 15:00-16:00. The monthly mean aerosol concentration in Yangquan was highest in January and lowest in August, and PM10 was also high in March and April. The most frequent surface wind directions in Yangquan are easterly and westerly due to the topography of the cross valley. The average concentrations of aerosols were highest in the calm wind weather. Furthermore, the dust weather caused by the westerly wind in spring and autumn and the easterly transport in winter also causes an increase in aerosol concentration in Yangquan. The backward trajectories in combination with the pollution characteristics showed that 26.2% of the pollution trajectories are in spring, 36.4% are in autumn, and 33.7% are in winter, and that these are mainly distributed in the southwest and southeast of Yangquan and also in the northeast in winter. There was significant fine particle transport on both sides of the mountains, and the trajectories originating from or passing through the west side of the Taihang Mountains also transport coarse particles. As indicated by the pollution trajectory, the westerly air transport has an impact on PM10 in excess of the standard rate. The easterly transport has larger noise and mainly affects the exceedance rate of PM2.5. The main potential source areas of aerosol pollution in Yangquan differ in different seasons. The potential source areas are to the southwest and southeast of Yangquan in spring, the southwest and south of Yangquan in autumn, and the south and east of Yangquan in winter. The areas with high PSCF and CWT in PM2.5 were in the southeast region, but those for PM10 were in the southwest region. The area southeast of Shanxi and the border area north of Henan are the main source areas. Based on the influence of aerosol pollution transmission in Yangquan, the cross-valley urban area is affected simultaneously by the areas east and west of the Taihang Mountains, especially by PM2.5 transport from east to west.

Temporal and Spatial Variations in Water Quality of Hanjiang River and Its Influencing Factors in Recent Years

Hanjiang River is the main water source and influence area of the Middle Route of the South to North Water Transfer Project. In recent years, the water quality and ecological environment in the middle and lower reaches of the Hanjiang River has become seriously degraded and water blooms occur frequently. Scientific identification of the temporal and spatial variations in water environment quality (and the main driving factors) has become an important management requirement for optimizing the upstream water transfer project. The temporal and spatial variations and influencing factors of water quality in the Hanjiang River basin were systematically analyzed, based on multi-source data and using the Daniel trend test, Mann Kendall test, K-means cluster analysis, dissimilarity analysis, and redundancy analysis. Results showed that: ① in recent years, the main stream of the Hanjiang River had generally good water quality, which was generally classified as class Ⅱ of GB 3838-2002, while the water quality of some sections in the middle and lower reaches was classified as class Ⅲ. However, the total phosphorus (TP) and total nitrogen (TN) load was relatively high, with 10 stations in the Hanjiang River basin showing averaged concentrations of 0.028-0.263 mg·L-1 and 0.630-1.852 mg·L-1, respectively, during 2014-2018. ② From 2004 to 2018, TP and TN at Zongguan station did not show significant variation, and other water quality indexes did not exhibit any regular patterns. The concentrations of TN, NH4+-N, and BOD5 in the dry season were higher than those in the wet season. In the wet season. the permanganate index showed different variation patterns, while TP concentration did not decrease significantly. ③ Different sections showed obvious differences in the variation of water quality indexes. However, the ten stations can be clustered into three categories: the upstream stations showed the best water quality, followed by the middle reaches, and the downstream stations showed the worst. The water quality at Xiaohe station improved significantly over the study period, which may be related to protection measures implemented in recent years, such as source control, emission reduction, and removal of aquaculture. ④ Water discharge and temperature were important factors affecting the water quality of the three regions in Hanjiang River. According to redundancy analysis, the contribution of discharge to water quality in the upstream and downstream areas was much larger, while the contribution of water temperature was greatest in the middle reaches of the river.

Rice supply flows and their determinants in China

While one has yet to be built in China, a rice supply flow network would provide essential information for stabilizing and optimizing food distribution and ensuring food security. Moreover, it is unclear how socioeconomic and natural environmental factors affect the rice supply flow. In this study, 35,768 random samples from the rice sales market were collected to build the rice flow network of China. The rice supply patterns at a regional and provincial level were revealed by the rice flow network. At the regional level, Northeast, Central, and East China are the main rice source areas, supplying almost all of China. At the provincial level, economically developed megacities, such as Beijing and Shanghai, and provinces with low temperatures like Tibet and Qinghai, rely heavily on imported rice. Determinant analysis shows that the rice supply patterns are mainly attributable to the cultivated area, primary industry employees, the permanent population, and tertiary industry proportion. These factors explain 75%, 59%, 48%, and 31%, respectively, of the rice supply spatial patterns. Furthermore, the interactions of cultivated area and temperature, cultivated area and primary industry proportion, and cultivated area and precipitation can explain 94%, 91%, and 89%, respectively, of the rice supply patterns. These findings reveal China's rice supply patterns and their determinants in recent years, providing essential information for optimizing the layout of rice production and ensuring food security in the future scenarios of climate change and socioeconomic development.