Directional coupler based on an elliptic cylindrical nanowire hybrid plasmonic waveguide.

We present what we believe is a novel directional coupler based on an elliptic cylindrical nanowire hybrid plasmonic waveguide. Using the finite element method, the electric field distributions of y-polarized symmetric and antisymmetric modes of the coupler are compared, and the coupling and transmission characteristics are analyzed; then the optimized separation distance between the two parallel waveguides, 100 nm, is obtained. This optimized architecture fits in the weak coupling regime. Furthermore, the energy transfer is studied, and the performances of the directional coupler are evaluated, including excess loss, coupling degree, and directionality. The results show that when the separation distance is set to 100 nm, the coupling length reaches the shorter value of 1.646 µm, and the propagation loss is as low as 0.076 dB/µm, and the maximum energy transfer can reach 80%. The proposed directional coupler features good energy confinement, ultracompact and low propagation loss, which has potential application in dense photonic-integrated circuits and other photonic devices.

[Retrieving Dustfall Distribution in Beijing City Based on Ground Spectral Data and Remote Sensing].

Dust-fall distribution of vegetation leaves can indicate the degree of air pollution; therefore the analysis of spatial characteristics of urban vegetation dust-fall has important practical significance for making more effective air pollution control policy. Based on the data of weight of dust, spectral reflectance and leaf area of Euonymus japonicus, Sophora japonica, poplar and davidiana collected in the main area of Beijing city, we compared the curve of spectrum of four plants "dust leaves" to "clean leaves"; the correlation analysis between leaf spectral reflectance ratio (Dust/Clean) of narrow band and satellite band was processed with the weight of dust-fall respectively, with application of four plants leaf data. Then, we built the regression model of the satellite band reflectance and NDVI with dustfall weight respectively, and we used the best model to retrieve the dust-fall distribution of vegetation coverage area in Beijing city, furthermore, we obtained the dust distribution of the whole Beijing city through interpolation. Finally, we carried out the rationality verification of the result by the land cover and land use of the high dust region, as well as the average concentration of PM10. The results showed that, dust leaves had an obviously lower reflectance than clean leaves in 780~1 300 nm which belonged to near-infrared bands; therewas a higher correlation between narrow band reflectance and dust-fall weight in 520~620 and 1 390~1 600 nm, up to -0.626; the coefficients of determination (R2) of inversion models were respectively 0.446 and 0.465,which were constructed by green band and NDVI of Landsat8 with dust-fall weight. Using the model established with NDVI to retrieving the dust-fall distribution of Beijing city, the results demonstrate that the distribution of dust-fall is high in north and low in south, high in east and low in west, high in downtown and low in the suburbs. This study offers a low-cost and effective method for investigating dust-fall distribution in urban area, and provides data support to analysis sources of pollution for the environmental protection department.

Elliptic cylindrical silicon nanowire hybrid surface plasmon polariton waveguide.

We researched an elliptic cylindrical silicon nanowire hybrid surface plasmon polariton waveguide and evaluated its mode characteristics using the finite element method software COMSOL. The waveguide consists of three parts: an elliptic cylindrical silicon nanowire, a silver film layer, and a silica covering layer between them. All of the components are surrounded by air. After optimizing the geometrical parameters of the waveguide, we can achieve the waveguide's strong field confinement (ranging from λ2/270 to λ2/27) and long propagation distances (119-485 µm). In order to further understand the impact of the waveguide's architecture on its performance, we also studied the ridge hybrid waveguide. The results show that the ridge waveguide has moderate local field confinement ranging from λ2/190 to λ2/20 and its maximum propagation distance is about 340 µm. We compared the elliptic cylindrical and ridge nanowire hybrid waveguides with the cylindrical hybrid waveguide that we studied before. The elliptic cylindrical waveguide achieves a better trade-off between reasonable mode confinement and maximum propagation length in the three waveguides. The researched hybrid surface plasmon polaritons waveguides are useful to construct devices such as a directional coupler and may find potential applications in photonic integrated circuits or other novel SPP devices.

Dustfall Heavy Metal Pollution During Winter in North China.

In order to study heavy metal pollution in dustfall during Winter in North China, forty-four dustfall samples were collected in North China Region from November 2013 to March 2014. Then forty trace elements content were measured for each sample by inductively coupled plasma-mass spectrometry. Finally, the contamination characteristics of the main heavy metals were studied through a multi-method analysis, including variability analysis, Pearson correlation analysis and principal component analysis. Results showed that the relative contents of cadmium (Cd), zinc (Zn), copper (Cu), bismuth (Bi), lead (Pb) exceeded the standards stipulated in Chinese soil elements background values by amazing 4.9 times. In this study, conclusions were drawn that dustfall heavy metal pollution in the region was mainly caused by transport pollution, metallurgy industrial pollution, coal pollution and steel industrial pollution.

Spatio-Temporal Variation Characteristics of PM2.5 in the Beijing-Tianjin-Hebei Region, China, from 2013 to 2018.

Air pollution, including particulate matter (PM2.5) pollution, is extremely harmful to the environment as well as human health. The Beijing-Tianjin-Hebei (BTH) Region has experienced heavy PM2.5 pollution within China. In this study, a six-year time series (January 2013-December 2018) of PM2.5 mass concentration data from 102 air quality monitoring stations were studied to understand the spatio-temporal variation characteristics of the BTH region. The average annual PM2.5 mass concentration in the BTH region decreased from 98.9 µg/m3 in 2013 to 64.9 µg/m3 in 2017. Therefore, China has achieved its Air Pollution Prevention and Control Plan goal of reducing the concentration of fine particulate matter in the BTH region by 25% by 2017. The PM2.5 pollution in BTH plain areas showed a more significant change than mountains areas, with the highest PM2.5 mass concentration in winter and the lowest in summer. The results of spatial autocorrelation and cluster analyses showed that the PM2.5 mass concentration in the BTH region from 2013-2018 showed a significant spatial agglomeration, and that spatial distribution characteristics were high in the south and low in the north. Changes in PM2.5 mass concentration in the BTH region were affected by both socio-economic factors and meteorological factors. Our results can provide a point of reference for making PM2.5 pollution control decisions.

[Concurrent Measurement of Wet and Bulk Deposition of Trace Metals in Urban Beijing].

To characterize the dry and wet deposition of atmospheric trace elements in urban Beijing, both active and passive samplers were used to collect bulk and wet sedimentation samples between May 2014 and April 2015.The concentrations of 19 trace elements (Na, Mg, Al, K, Ca, V, Cr, Mn, Fe, Cu, Zn, As, Se, Mo, Cd, Sb, Tl, Th, and U) in the samples were analyzed by inductively coupled plasma mass spectrometry (ICP-MS). The results show that the concentrations of metals in bulk deposition samples[7160.68 µg·L-1 (Ca)-0.02 µg·L-1 (Th)] were generally higher than those in wet deposition samples[4237.74 µg·L-1 (Ca)-0.01 µg·L-1 (Th)], but the enrichment factors of each metal in the two kinds of samples were less different. Of note, the enrichment factors of Cu, As, Tl, Zn, Cd, Se, and Sb were all larger than 100, thus indicating that these heavy metals were mainly from anthropogenic sources. The statistical analysis of the air mass trajectory shows that the precipitation chemistry in urban Beijing is mainly affected by southward air flows. The air mass originating from the southwest region always had higher concentrations of Ca, Mg, Fe, Al, Cu, Mo, U, and Th, whereas the air mass from the south had higher concentrations of K, Zn, Mn, Sb, Cd, and Tl. During the observation period, the bulk deposition fluxes of metals varied from 3591.35 mg·(m2·a)-1 (Ca)-0.01 mg·(m2·a)-1 (Th), and wet deposition fluxes varied from 1847.78 mg·(m2·a)-1 (Ca)-0.01 mg·(m2·a)-1 (Th). The dry deposition fluxes of the 19 metals varied from 1743.57 mg·(m2·a)-1 (Ca)-0.01 mg·(m2·a)-1 (Th). The particle size has important implications in the evaluation of the relative importance of dry deposition versus wet deposition during the scavenging of trace elements in air.

[Enrichment Levels and Comprehensive Pollution Assessment of Dust Heavy Metals in Winter in Beijing].

Dust reflects the natural subsidence of particles and is thus generally accepted as an important environmental indicator. Dust heavy metals find their way into soil or water via atmospheric deposition, potentially damaging plants, aquatic organisms, as well as human beings. In order to study the concentration levels, enrichment degrees, and comprehensive pollution characteristics of the dust heavy metals Cd, Cr, Pb, Cu, Zn, Ni, Co, V, Bi, and Mo in winter in Beijing, 49 groups of dust samples were collected from different locations within the city from November 2013 to March 2014. Heavy metal content (mass percentage) was then measured using Elan DRC Ⅱ type inductively-coupled plasma mass spectrometry (ICP-MS). Results showed that the average content of Cd, Bi, and Mo was less than 10 mg·kg-1, that of Co, Ni, and V was between 10 and 100 mg·kg-1, while that of Pb, Cr, Cu, and Zn was more than 100 mg·kg-1. The amount of Cd, Zn, and Cu in dust samples was generally higher than their secondary standard values in the soil environment. The secondary standard excess rates of Cd, Zn, and Cu were 100%, 97%, and 93.9% in urban environments, and 100%, 100%, and 81.2% in suburban environments, respectively. Results also indicated slight enrichment of Bi, Cu, Ni, and Pb, mainly derived from crustal or soil sources, while Cd, Cr, Mo, and Zn, exhibited mild enrichment, caused by a combination of natural and artificial sources. The paper proposes a "dust heavy metal comprehensive pollution index" model, based on the traditional single pollution assessment method, so as to explore comprehensive pollution characteristics of dust heavy metals in Beijing. Results for the dust heavy metal comprehensive pollution index in Beijing City were in the order of Cd > Zn > Cu > Pb > Cr > Ni > V > Co. Cd, Zn, Cu, and Pb were identified as key pollution factors, with Cd and Zn as primary factors. Results for the dust heavy metal comprehensive pollution index in Beijing suburbs was Cd > Zn > Cu > Pb > Cr > Ni > Co > V. Cd, Zn, Cu, Pb, and Cr were key pollution factors, with Cd and Zn as primary factors.

Comparison of Ground-Based PM2.5 and PM10 Concentrations in China, India, and the U.S.

Urbanization and industrialization have spurred air pollution, making it a global problem. An understanding of the spatiotemporal characteristics of PM2.5 and PM10 concentrations (particulate matter with an aerodynamic diameter of less than 2.5 µm and 10 µm, respectively) is necessary to mitigate air pollution. We compared the characteristics of PM2.5 and PM10 concentrations and their trends of China, India, and the U.S. from 2014 to 2017. Particulate matter levels were lowest in the U.S., while China showed higher concentrations, and India showed the highest. Interestingly, significant declines in PM2.5 and PM10 concentrations were found in some of the most polluted regions in China as well as the U.S. No comparable decline was observed in India. A strong seasonal trend was observed in China and India, with the highest values occurring in winter and the lowest in summer. The opposite trend was noted for the U.S. PM2.5 was highly correlated with PM10 for both China and India, but the correlation was poor for the U.S. With regard to reducing particulate matter pollutant concentrations, developing countries can learn from the experiences of developed nations and benefit by establishing and implementing joint regional air pollution control programs.

Analysis of the Characteristics and Sources of Carbonaceous Aerosols in PM2.5 in the Beijing, Tianjin, and Langfang Region, China.

PM2.5 samples from Beijing, Tianjin, and Langfang were simultaneously collected from 20 November 2016 to 25 December 2016, and the organic carbon (OC) and elemental carbon (EC) content in the samples were measured and analyzed. The pollution characteristics and sources of OC and EC in atmospheric PM2.5 for three adjacent cities were discussed. The average mass concentrations of OC in PM2.5 in Beijing, Tianjin, and Langfang were 27.93 ± 23.35 µg/m³, 25.27 ± 12.43 µg/m³, and 52.75 ± 37.97 µg/m³, respectively, and the mean mass concentrations of EC were 6.61 ± 5.13 µg/m³, 6.14 ± 2.84 µg/m³, and 12.06 ± 6.81 µg/m³, respectively. The average mass concentration of total carbon (TC) accounted for 30.5%, 24.8%, and 49% of the average mass concentration of PM2.5 in the atmosphere. The total carbonaceous matter (TCA) in Beijing, Tianjin, and Langfang was 51.29, 46.57, and 96.45 µg/m³, respectively. The TCA was the main component of PM2.5 in the region. The correlation between OC and EC in the three cities showed R² values of 0.882, 0.633, and 0.784 for Beijing, Tianjin, and Langfang, respectively, indicating that the sources of urban carbonaceous aerosols had good consistency and stability. The OC/EC values of the three sampling points were 4.48 ± 1.45, 4.42 ± 1.77, and 4.22 ± 1.29, respectively, considerably greater than 2, indicating that the main sources of pollution were automobile exhaust, and the combustion of coal and biomass. The OC/EC minimum ratio method was used to estimate the secondary organic carbon (SOC) content in Beijing, Tianjin and Langfang. Their values were 10.73, 10.71, and 19.51, respectively, which accounted for 38%, 42%, and 37% of the average OC concentration in each city, respectively. The analysis of the eight carbon components showed that the main sources of pollutants in Beijing, Tianjin, and Langfang were exhaust emissions from gasoline vehicles, but the combustion of coal and biomass was relatively low. The pollution of road dust was more serious in Tianjin than in Beijing and Langfang. The contribution of biomass burning and coal-burning pollution sources to atmospheric carbon aerosols in Langfang was more prominent than that of Beijing and Tianjin.

Characteristics of PM2.5 Chemical Compositions and Their Effect on Atmospheric Visibility in Urban Beijing, China during the Heating Season.

Beijing, which is the capital of China, suffers from severe Fine Particles (PM2.5) pollution during the heating season. In order to take measures to control the PM2.5 pollution and improve the atmospheric environmental quality, daily PM2.5 samples were collected at an urban site from 15 November to 31 December 2016, characteristics of PM2.5 chemical compositions and their effect on atmospheric visibility were analyzed. It was found that the daily average mass concentrations of PM2.5 ranged from 7.64 to 383.00 µg m-3, with an average concentration of 114.17 µg m-3. On average, the Organic Carbon (OC) and Elemental Carbon (EC) contributed 21.39% and 5.21% to PM2.5, respectively. Secondary inorganic ions (SNA: SO4²- + NO3- + NH4⁺) dominated the Water-Soluble Inorganic Ions (WSIIs) and they accounted for 47.09% of PM2.5. The mass concentrations of NH4⁺, NO3- and SO42- during the highly polluted period were 8.08, 8.88 and 6.85 times greater, respectively, than during the clean period, which contributed most to the serious PM2.5 pollution through the secondary transformation of NO2, SO2 and NH3. During the highly polluted period, NH4NO3 contributed most to the reconstruction extinction coefficient (b'ext), accounting for 35.7%, followed by (NH4)2SO4 (34.44%) and Organic Matter (OM: 15.24%). The acidity of PM2.5 in Beijing was weakly acid. Acidity of PM2.5 and relatively high humidity could aggravate PM2.5 pollution and visibility impairment by promoting the generation of secondary aerosol. Local motor vehicles contributed the most to NO3-, OC, and visibility impairment in urban Beijing. Other sources of pollution in the area surrounding urban Beijing, including coal burning, agricultural sources, and industrial sources in the Hebei, Shandong, and Henan provinces, released large amounts of SO2, NH3, and NO2. These, which were transformed into SO42-, NH4⁺, and NO3- during the transmission process, respectively, and had a great impact on atmospheric visibility impairment.

Concentration Levels, Pollution Characteristics and Potential Ecological Risk of Dust Heavy Metals in the Metropolitan Area of Beijing, China.

This study aims to investigate the concentration levels, pollution characteristics and the associated potential ecological risks of the heavy metals found in dust in the metropolitan area of Beijing, China during the winter. Dust samples were collected at 49 different spatial locations of Beijing's metropolitan area from November 2013 to January 2014, in which the concentration levels of Cd, Cr, Pb, Cu, Zn, Ni, Co, V, Bi and Mo were measured by Elan DRC II type inductively coupled plasma mass spectrometry (ICP-MS). Test results showed that the concentrations of dust heavy metals Pb, Cr, Cu and Zn in the urban areas (147.1 mg·kg-1, 195.9 mg·kg-1, 239.2 mg·kg-1 and 713.2 mg·kg-1) were significantly higher than those in the suburbs (91.6 mg·kg-1, 125.1 mg·kg-1, 131.9 mg·kg-1 and 514.5 mg·kg-1). Enrichment factors and the geo-accumulation index were used to describe the pollution characteristics of dust heavy metals in urban and suburban areas. Results indicated that Zn and Cu were moderately polluting in both urban and suburban areas, Cd was severely polluting in urban areas and heavily polluting in the suburbs. Furthermore, potential ecological risk assessment revealed that the degrees of ecological harm of dust heavy metals were very strong in both urban and suburban areas, but especially in urban areas. The potential ecological risk of heavy metal Cd, whose single factor of ecological damage was extremely strong, accounted for about 90% of the total ecological risk.

Fine Particulate Matter Pollution and Hospital Admissions for Respiratory Diseases in Beijing, China.

Fine particulate matter has become the premier air pollutant of Beijing in recent years, enormously impacting the environmental quality of the city and the health of the residents. Fine particles with aerodynamic diameters of 0~0.3 µm, 0.3~0.5 µm, and 0.5~1.0 µm, from the yeasr 2007 to 2012, were monitored, and the hospital data about respiratory diseases during the same period was gathered and calculated. Then the correlation between respiratory health and fine particles was studied by spatial analysis and grey correlation analysis. The results showed that the aerial fine particulate matter pollution was mainly distributed in the Zizhuyuan sub-district office. There was a certain association between respiratory health and fine particles. Outpatients with respiratory system disease in this study area were mostly located in the southeastern regions (Balizhuang sub-district office, Ganjiakou sub-district office, Wanshoulu sub-district office, and Yongdinglu sub-district office) and east-central regions (Zizhuyuan sub-district office and Shuangyushu sub-district office) of the study area. Correspondingly, PM1 (particulate matter with aerodynamic diameter smaller than 1.0 um) concentrations in these regions were higher than those in any other regions. Grey correlation analysis results showed that the correlation degree of the fine particle concentration with the number of outpatients is high, and the smaller fine particles had more obvious effects on respiratory system disease than larger particles.

Pollution Characteristics and Health Risk Assessment of Airborne Heavy Metals Collected from Beijing Bus Stations.

Airborne dust, which contains high levels of toxic metals, is recognized as one of the most harmful environment component. The purpose of this study was to evaluate heavy metals pollution in dustfall from bus stations in Beijing, and to perform a risk assessment analysis for adult passengers. The concentrations of Cd, Co, Cr, Cu, Mo, Ni, Pb, V and Zn were determined by inductively coupled plasma mass spectroscopy (ICP-MS). The spatial distribution, pollution level and potential health risk of heavy metals were analyzed by Geographic Information System (GIS) mapping technology, geo-accumulation index and health risk assessment model, respectively. The results indicate that dust samples have elevated metal concentrations, especially for Cd, Cu, Pb and Zn. The nine metals can be divided into two categories in terms of spatial distribution and pollution level. Cd, Cr, Cu, Mo, Pb and Zn reach contaminated level and have similar spatial patterns with hotspots distributed within the Fifth Ring Road. While the hot spot areas of Co and V are always out of the Fifth Ring Road. Health risk assessment shows that both carcinogenic and non-carcinogenic risks of selected metals were within the safe range.

[Distribution Characteristics and Source Analysis of Dustfall Trace Elements During Winter in Beijing].

The dustfall content is one of the evaluation indexes of atmospheric pollution. Trace elements especially heavy metals in dustfall can lead to risks to ecological environment and human health. In order to study the distribution characteristics of trace elements, heavy metals pollution and their sources in winter atmospheric dust, 49 dustfall samples were collected in Beijing City and nearby during November 2013 to March 2014. Then the contents (mass percentages) of 40 trace elements were measured by Elan DRC It type inductively coupled plasma mass (ICP-MS). Test results showed that more than half of the trace elements in the dust were less than 10 mg x kg(-1); about a quarter were between 10-100 mg x kg-1); while 7 elements (Pb, Zr, Cr, Cu, Zn, Sr and Ba) were more than 100 mg x kg(-1). The contents of Pb, Cu, Zn, Bi, Cd and Mo of winter dustfall in Beijing city.were respectively 4.18, 4.66, 5.35, 6.31, 6.62, and 8.62 times as high as those of corresponding elements in the surface soil in the same period, which went beyond the soil background values by more than 300% . The contribution of human activities to dustfall trace heavy metals content in Beijing city was larger than that in the surrounding region. Then sources analysis of dustfall and its 20 main trace elements (Cd, Mo, Nb, Ga, Co, Y, Nd, Li, La, Ni, Rb, V, Ce, Pb, Zr, Cr, Cu, Zn, Sr, Ba) was conducted through a multi-method analysis, including Pearson correlation analysis, Kendall correlation coefficient analysis and principal component analysis. Research results indicated that sources of winter dustfall in Beijing city were mainly composed of the earth's crust sources (including road dust, construction dust and remote transmission of dust) and the burning of fossil fuels (vehicle emissions, coal combustion, biomass combustion and industrial processes).

[Study on influence of traffic and meteorological factors on inhalable particle matters of different size].

To study the effects of meteorological and traffic factors on the PM2.5 and PM10 concentrations, 28 samples were taken in the Third Ring Road of Beijing, and dust fall weight, velocity of vehicle, traffic volume, temperature, humidity, wind speed, PM2.5 and PM10 concentration data were collected for these samples. Analysis of the collected data on dust fall weight indicated that the traffic had a significant impact on the air quality. The average dust fall weights in the road and away from the traffic source were 0. 284g and 0. 016 g, respectively. The results of the partial experiment indicated that concentrations of PM2.5 and PM10 in residential areas were lower than those in road, furthermore, the PM2.5 at night was often higher than that during daytime, and the mean values of the difference in PM2.5 and PM10 were 101074 n.(cf)-1 and 15386 n.(cf)-1, respectively. Through analysis using the best subset prediction model, it was indicated that PM2.5 and PM10 were both most significantly influenced by temperature and humidity, followed by wind speed, velocity of vehicle and traffic volume. Comparing with PM10, the velocity of vehicle, traffic volume and wind speed had a more significant influence on PM2.5.