Cooling Performance and Indoor Air Quality Characteristics of an Earth Air Tunnel Cooled Building

Most of the modern air-conditioned buildings have a low fresh air supply to reduce energy consumption. This results in a poor indoor air quality (IAQ) and a 30–200% higher sick building syndrome than that of a naturally ventilated building. Alternatively, energy-efficient and eco-friendly earth air tunnel system (EATS) provides a good IAQ because of the sufficient fresh air supply. This paper presents the cooling performance and IAQ characteristics of a sparsely occupied building supported with an EATS. The building was monitored for the concentration of fine and coarse particulate matter (PM), carbon dioxide (CO₂) and carbon monoxide (CO), temperature distribution and relative humidity (RH) in September and October 2012. The average PM₁₀, PM_2.5 and PM₁ concentrations were 6.77, 6.11 and 3.17 μg/m³ respectively when the EATS was operated. These are marginally higher compared to that when the EATS was not operated. The average indoor CO₂ level, air temperature and RH were 418 ppm, 26.5 °C and 58.2% respectively when the EATS was operated. The diurnal indoor CO₂ trend relates well with photosynthetic and anthropogenic activities in and around the building. The CO₂ and PM concentrations correlate well with indoor air temperature and RH with a time lag.     

Vertical Profile of Particulate Matter Concentrations in Indoor Air (Case Study: Karaj,Iran)

Particulate matter is one of the most significant pollutants in indoor environments. The study of vertical profile concentration coefficients of different particulates leads us to figure out the most accurate pattern of vertical profile change of these hazardous particles. In this case, three different sizes of particulate vertical profile patterns, PM_1.0, PM_2.5, and PM₁₀, were evaluated in indoors in the city of Karaj. Samplings of first and fourth floors of 5 buildings located in different areas of Karaj were conducted constantly during 2011. The results of Mahestan Station illustrate the highest average concentration of PM₁₀ (173 µg/m³) whereas the RajaieShahr Station measurements indicates the highest average concentrations of PM_2.5(66 µg/m³) and also PM_1.0(51 µg/m³). Generally, the concentrations of the particulates in the first floors were higher than that in the fourth floors, and according to the air evaluation stations, all the particulates including PM_1.0, PM_2.5, and PM₁₀ had concentrations higher than the annual standard.     

Cleanable Air Filter Transferring Moisture and Effectively Capturing PM2.5

The lethal danger of particulate matter (PM) pollution on health leads to the development of challenging individual protection materials that should ideally exhibit a high PM_2.5 purification efficiency, low air resistance, an important moisture‐vapor transmission rate (MVTR), and an easy‐to‐clean property. Herein, a cleanable air filter able to rapidly transfer moisture and efficiently capture PM_2.5 is designed by electrospinning superhydrophilic polyacrylonitrile/silicon‐dioxide fibers as the adsorption–desorption vector for moisture‐vapor, and hydrophobic polyvinylidene fluoride fibers as the repellent components to avoid the formation of capillary water under high humidity. The desorption rate of water molecules increases from 10 to 18 mg min^?1, while the diameters of polyacrylonitrile fibers reduce from 1.02 to 0.14 µm. Significantly, by introducing the hydroxyl on the surface of polyacrylonitrile nanofibers, rapid adsorption–desorption of the water molecules is observed. Moreover, by constructing a hydrophobic to super‐hydrophilic gradient structure, the MVTR increases from 10 346 to 14 066 g m^?2 d^?1. Interestingly, the prepared fibrous membranes is easy to clean. More importantly, benefiting from enhanced slip effect, the resultant fibrous membranes presented a low air resistance of 86 Pa. A field test in Shanghai shows that the air filter maintains stable PM_2.5 purification efficiency of 99.99% at high MVTR during haze event.     

Atmospheric Fine and Coarse Mode Aerosols at Different Environments of India and the Bay of Bengal During Winter-2014: Implications of a Coordinated Campaign

In this paper, we present mass concentrations of particulate matter [PM_2.5, PM₁₀ size fractions and total suspended particulates (TSP)] measured simultaneously over land stations (Kullu, Patiala, Delhi, Ajmer, Agra, Lucknow, Varanasi, Giridih, Kolkata, Darjeeling, Jorhat, Itanagar, Imphal, Bhubaneswar, and Kadapa), mostly distributed across the Indo-Gangetic plain (IGP) of India as well as in the marine atmosphere over Bay of Bengal (BoB) in the period from 20 January to 3 February, 2014. The main objective of this study was to quantify the continental outflow of particulates (PM_2.5, PM₁₀ and TSP) from IGP and associated regions into the BoB along with low level north-east wind flow during winter monsoon period. The present study provides a glimpse of the aerosol loading over the IGP region. During this campaign, the highest average PM_2.5 (187.8 ± 36.5 µg m^?3, range 125.6–256.2 µg m^?3), PM₁₀ (272.6 ± 102.9 µg m^?3, range 147.6–520.1 µg m^?3) and TSP (325.0 ± 71.5 µg m^?3, range 220.4–536.6 µg m^?3) mass concentrations were recorded at Varanasi, Kolkata and Lucknow over middle and lower IGP regions. The PM_2.5 (average 41.3 ± 11.9 µg m^?3; range 15.0–54.4 µg m^?3), PM₁₀ (average 53.9 ± 18.9 µg m^?3; range 30.1–82.1 µg m^?3) and TSP (average 78.8 ± 29.7 µg m^?3; range 49.1–184.5 µg m^?3) loading over BoB were found to be comparable to land stations and suggests possible continental outflow. Over the continental region, the highest PM_2.5/PM₁₀ ratio was recorded at Delhi (0.87). The PM_2.5/PM₁₀ ratio over BoB (0.77) was found to be quite high and comparable to Varanasi (0.80) and Agra (0.79).     

Traceability Issue in PM2.5 and PM10 Measurements

Nowadays particle size and mass concentration measurements are the important parameter of the ambient air quality standards of several countries. The regulatory limits of mass concentration of particulate matter (PM) for the size classes of PM_2.5 and PM₁₀, i.e., particle sizes of less than or equal to 2.5 and 10 μm in aerodynamic diameter, respectively in air are defined on yearly and hourly time-weighted-average basis. However, these limits are different in different regulations of the countries. Both of the parameters relate with the human health, climate and other issues, therefore accurate and precise measurement of these parameters are very important. Despite this, so far not much work has progressed in national metrology institutes (NMIs) worldwide on calibration and traceability issue of PM measurements. In this paper in context of PM measurement traceability, we present systematically the (1) air quality regulation in different countries, (2) reference methods for size and mass measurements, (3) variation/error and limitations of PM measurements based on the current results in this study and previously published results, (4) current status of PM size and mass calibration facility, (5) expected uncertainty in PM measurements, (6) add-on uncertainty in other parameters of national ambient air quality standards due to PM measurements, (7) where does traceability of PM issue stand against other parameters of air quality standards and its impact on health and climate, (8) NMIs working on this issue, (9) status at Bureau International des Poids et Mesures (BIPM), France and (10) conclusion. The aim of this paper is to better understand the importance of international system of units (SI) traceability issue in PM measurements, so wherever and whenever it is measured, should be acceptable everywhere, and data should be comparable for improving air quality and thus the quality of life. Funding agencies should be aware of this issue, and accept the results from the principle investigators and team only when their results have the traceability link to SI. NMIs should make program to involve industries in gas and aerosol metrology work to fulfill the requirement of calibration and standards. The regulatory authorities/ministry should work together with NMIs to improve the data quality of ambient measurements. This will greatly help to better make the policies and decisions on the related impacts. These were also the ultimate goals of “one-day pre-AdMet workshop” organized at National Physical Laboratory, New Delhi, India on February 20th, 2013.     

Measurements of Particulate (PM2.5), BC and Trace Gases Over the Northwestern Himalayan Region of India

Ambient trace gases (NH₃, NO, NO₂ and SO₂) and black carbon (BC) were measured along with particulate matter (PM_2.5) over the northwestern Himalayan region (Palampur, Kullu, Shimla, Solan and Nahan) of Himachal Pradesh (HP), India in a campaign mode during 12–22 March 2013 to evaluate the ambient air quality of the region. The average mixing ratio of ambient NH₃, NO, NO₂ and SO₂ were recorded as 7.1 ± 2.6, 3.1 ± 1.3, 3.9 ± 1.4 and 1.7 ± 0.7 ppb respectively over the northwestern Himalayan region. The average concentration of BC was estimated as 2.2 ± 0.5 µg m^?3 over the region whereas average concentration of PM_2.5 mass was estimated as 41.8 ± 7.9 µg m^?3. The spatial variation of ambient trace gases (NH₃, NO, NO₂ and SO₂), BC and PM_2.5 over the northwestern Himalayan region, India reveals that the region is mainly influenced by local activities, i.e., tourism activities, agricultural activities, biomass burning and vehicular emission. A significant positive linear correlation of NH₃ and NH₄ ⁺ with SO₄ ^2?, NO₃ ^? and Cl^? (NH₄ ⁺ vs. SO₄ ^2? , r ² = 0.652; NH₄ ⁺ vs. NO₃ ^?, r ² = 0.701; and NH₄ ⁺ vs. Cl^?, r ² = 0.627) of the PM_2.5 indicates the possible formation of (NH₄)₂SO₄, NH₄NO₃ and NH₄Cl aerosols over the region.     

Statistical Model to Study the Effect of Agriculture Crop Residue Burning on Healthy Subjects

Pulmonary function test (PFT) values of 50 healthy subjects and levels of pollutants like suspended particulate matter (SPM), PM₁₀, PM_2.5 in ambient air were continually investigated from February 2007 to January 2010 at Patiala, Punjab (India). Significant decrease in PFTs were observed with increase in concentration levels of pollutants during wheat and rice crop residue burning in the fields. In the present paper a new statistical model on field crop residue burning and PFT has been proposed. The model is based on multiple ordinary least square regression method. It can predict values of PFTs as a function of some parameters of air pollutants. Monthly average values of different variables are used for the purpose of designing four different models. These models were tested by parameters like randomness of residual, relationship of residual with independent variables, etc. The final accepted models could predict up to 88 % variation in the values of force vital capacity and force expiratory volume and up to 77 % variation in peak expiratory flow and force expiratory flow with the corresponding changes in the SPM, PM₁₀, PM_2.5 and temperature respectively. This model can be used as a tool for measurement of risk assessment due to air pollution in future.     

Multi-Unit Needleless Electrospinning for One-Step Construction of 3D Waterproof MF-PVA Nanofibrous Membranes as High-Performance Air Filters

The airborne particulate matter (PM) seriously threatens people's health. Personal protective equipment with electrospun nanofibers is an effective method to make people away from air pollutants. Herein, 3D waterproof melamine-formaldehyde polyvinyl alcohol (MF-PVA) nanofibrous membranes are fabricated by a one-step method combining multi-unit needleless electrospinning and a thermal treatment device in a line. 3D nanofibrous structures can be controlled by adjusting the solution concentration of each unit. The PVA nanofibrous membranes become waterproof after cross-linking with MF resin in the following thermal treatment device. The optimized MF-PVA nanofibrous membrane shows excellent air filtration performance (97.3% for PM_0.3, 100% for PM_1.0, and 100% for PM_2.5) and low air resistance (76 Pa). These 3D waterproof MF-PVA nanofibrous membranes exhibit ultra-stable performance in various practical environments.     

Catalysis and kinetics of diesel soot oxidation over nano-size perovskite catalyst

The present work reports a comparative study of perovskite catalysts prepared by sol–gel (SG) and reactive grinding (RG) methods for the diesel soot/PM oxidation. The optimal formulated perovskite, La_0.9Sr_0.1Co_0.5Fe_0.5O₃ (Cat-D) prepared by RG with a ZnO additive and reactively calcined (RC) in a 4.6% CO–air mixture, exhibited the highest surface area (94.8 m²/g), smallest crystallites (8.4 nm) and the best activity for the PM oxidation. Oxidation was initiated at ～ 235 °C, reached a peak at ～ 276 °C and was completed at 318 °C. Catalysts were characterized by N₂ sorption, XRD, FTIR and SEM. The high activity of Cat-D may be related to its unusual characteristics arising from RG and RC. Indeed, the severe mechano-chemical deformation during ball-milling leads to fractures and cold welding, in addition to oxygen-deficient structure produced by RC resulting high density of active sites in nano-size catalyst. The kinetics of air oxidation of the PM over Cat-D under isothermal condition is reported in the present paper. Kinetics data were composed under the environment of free heat and mass transfer limitations in a specifically designed mini-semi-batch reactor. With the intention of defining the kinetic model, activation energy and Arrhenius constant of the soot oxidation with high air flow rate, pseudo-first-order reaction was presumed. The kinetics for PM oxidation in the temperature range 325–355 °C can be represented by the following rate expression: \({\text{Rate}}\left( r \right) = 6.46 \times 10^{10}\exp \, \left( { - 101.08/RT} \right) \, \left( {\text{m}} \right){\text{ g}}\,PM/{\text{g}}\,{\text{cat}}.{\text{s}}\) The activation energy was found to be 101.08 kJ/mol.     

Infrared spectroscopic characterization of Na5Lu9F32 single crystals doped with various Er3+ concentrations

This work reports on optical spectra of Na₅Lu₉F₃₂ single crystals doped with various Er³⁺ concentrations from 0.5 to 5 mol%. In our improved Bridgman method, the X-ray powder diffractions were investigated and optical parameters were also calculated by the Judd–Ofelt theory. Results showed that Er³⁺ ions entered the Lu³⁺ sites successfully without causing any obvious peak changes, and the doping concentration of Er³⁺ had important influence on the Er³⁺ local structure in Na₅Lu₉F₃₂ crystals. The maximum emission intensities of ~1.5 and ~2.7 μm were obtained in present research when the doping concentration of Er³⁺ were 4 and 5 mol%, respectively, under the excitation of 980 nm LD. In these doping concentration, the maximum emission cross-sections were calculated to be 1.37 × 10^?20 cm² (~1.5 μm) and 2.1 × 10^?20 cm² (~2.7 μm). The gain cross-section at 2.7 μm was also estimated according to the absorption and emission cross section spectra. All these spectroscopic characterizations suggested that this fluoride crystal would possess promising applications in infrared lasers.     

Influence of clean air and inlet configuration on the performance of slit nozzle virtual impactor

A two-partitioned horizontal inlet was developed for improving the collection efficiency and minimizing the wall loss problem in slit virtual impactor. The two-partitions were provided to simultaneously supply both aerosol and clean air to the virtual impactor. Both numerical and experimental investigations were carried out on the developed inlet configuration by considering different flowrate ratios of aerosol to clean air. The horizontal inlet was helpful in reducing the cutoff diameter, whereas the clean air prevented the particle deposition on the virtual impactor walls. The performance of two-partitioned horizontal inlet was compared with the conventional vertical inlet configuration for PM_2.5, PM₅ and PM₁₀ virtual impactors. All the operating conditions and geometric parameters, such as the inlet flowrate; the width of collection nozzle; the width, length and span of acceleration nozzle; and the distance between collection and acceleration nozzles, were kept the same and only the inlet configuration was changed. The major-to-total flowrate ratio was kept at 0.9 and minor-to-total flowrate ratio at 0.1. It was observed that by using the two-partitioned horizontal inlet configuration, the cutoff diameters for PM_2.5, PM₅ and PM₁₀ virtual impactors, were reduced by 16%, 10% and 11%, respectively, while the wall loss of particles near the cutoff size in all three cases were reduced from 16% to about 1%.     

Effect of nano-Calcium Carbonate on microcellular foaming of polypropylene

Using supercritical carbon dioxide as the physical foaming agent, a new batch process was carried out to prepare microcellular polypropylene (PP) and polypropylene/nano-Calcium Carbonate (PP/nano-CaCO₃) foams. Four concentrations of nano-CaCO₃, 3, 5, 7, and 10 wt% were used. The cell structure of foams and advantages of this new process were investigated and explained by thermal properties. Results showed that the foamed PP/5 wt% nano-CaCO₃ produced a microcellular foam with the minimum mean cell diameter (9.55 μm) and maximum cell density (1.50 × 10⁹ cells/cm³) among the four blends. Some unfoamed regions were observed in nanocomposite foams because nano-CaCO₃ could accelerate crystallization in cooling and cryostat stage. The new process took much less time (2.5 h) to foam and had much broader foaming temperature range (about 55 °C). But the foaming temperature range decreased after blending nano-CaCO₃ into PP matrix because nano-CaCO₃-induced isothermal and non-isothermal crystallization at higher temperature. In addition, the cell growth effect on variations of volume expansion ratio in PP/nano-CaCO₃ nanocomposites could be neglected comparing with the heterogeneous cell nucleation effect.     

Investigating the impact of urban grade-separation on pedestrian PM2.5 exposure

For urban intersections, grade separations have been deemed a way of mitigating traffic congestion. However, the environmental impact of various grade separations, especially on pedestrian exposure to traffic-related air pollution, is unknown. Particulate matter of 2.5 µm or less (PM_2.5) near roadsides comes mainly from vehicle emissions and has negative respiratory health effects. Pedestrian PM_2.5 exposure at ground level at different types of intersection and are studied and compared here. Based on realistic survey data at a current at-grade intersection, and reasonable assumptions about traffic speed and volume changes, MOVES modeling software used the highest resolution approach of operating mode distribution to calculate PM_2.5 emission inventory for three scenarios: at-grade intersection, overpass grade separation, and underpass grade separation. Pedestrian PM_2.5 exposure concentrations were estimated using the AERMOD model. The results of the case study show that both underpass and overpass intersections largely decrease pedestrian PM_2.5 exposure, at almost the same amplitude. From the viewpoint of regional environmental impacts, however, the underpass-type intersection is recommended for replacing the at-grade intersection, in order to both reduce traffic congestion and better contain pollution. The findings of this research indicate that, as three-dimensional urban transportation design is becoming a more popular measure for relieving traffic congestion, environmental analysis will become an increasingly critical part of intersection design.     

High‐Temperature Particulate Matter Filtration with Resilient Yttria‐Stabilized ZrO2 Nanofiber Sponge

Particulate matter (PM) is a major air pollutant in many regions, jeopardizing ecosystems and public health. Filtration at pollutant source is one of the most important ways to protect the environment, however, considering the high‐temperature exhaust gas emissions, effective removal of PM and related pollutants from their sources remains a major challenge. In this study, a resilient, heat‐resisting, and high‐efficiency PM filter based on yttria‐stabilized ZrO₂ (YSZ) nanofiber sponge produced with a scalable solution blow spinning process is reported. The porous 3D sponge composed of YSZ nanofibers is lightweight (density of 20 mg cm^?3) and resilient at both room temperature and high temperatures. At room‐temperature conditions, the YSZ nanofiber sponge exhibits 99.4% filtration efficiency for aerosol particles with size in the range of 20–600 nm, associated with a low pressure drop of only 57 Pa under an airflow velocity of 4.8 cm s^?1. At a high temperature of 750 °C, the ceramic sponge maintains a high filtration efficiency of 99.97% for PM_0.3–2.5 under a high airflow velocity of 10 cm s^?1. A practical vehicle exhaust filter to capture particles with filtration efficiency of >98.3% is also assembled. Hence, the YSZ nanofiber sponge has enormous potential to be applied in industry.     

Coagulation and Collection of PM2.5 Based on a Stack Coagulator

China recently put forward stronger requirements for PM2.5 emission in 2012. Electrostatic precipitators have relatively low efficiency for the collection of submicron particle, especially for PM2.5. An alternate way to increase its efficiency is to enforce the coagulation and, thereby, form larger particles. In this work, we propose an efficient way to enhance the coagulation between oppositely charged particles by using a stack coagulator. Firstly, in order to explore the impact of the bipolar charging and coagulation to the separation efficient of PM2.5, we use system modeling and simulation to explore the whole charge-coagulation-collection process of PM2.5. The results show that the coagulation rate of bipolarly charged particles can be increased by a factor of 10² ～ 10⁴ compared to the neutral particles and the collection efficiency of dust particles increases as the particle size grows. Subsequently, via the dust particles coagulation experiments, the emission rate chart and emission reduction charts of PM2.5 are plotted, which indicate that the average emission reduction of PM2.5 is almost 85%.     

Meteorological variations of PM2.5/PM10 concentrations and particle-associated polycyclic aromatic hydrocarbons in the atmospheric environment of Zonguldak, Turkey

Airborne particulate matter (PM_2.5 and PM₁₀) concentrations were measured in Zonguldak, Turkey from January to December 2007, using dichotomous Partisol 2025 sampler. Collected particulate matter was analyzed for 14 selected polycyclic aromatic hydrocarbons (PAHs) by high-performance liquid chromatography with fluorescence detection (HPLC-FL). The seasonal variations of PM_2.5 and PM₁₀ concentrations were investigated together with their relationships with meteorological parameters. The maximum daily concentrations of PM_2.5 and PM₁₀ reached 83.3 μg m⁻³ and 116.7 μg m⁻³ in winter, whereas in summer, they reached 32.4 μg m⁻³ and 66.7 μg m⁻³, respectively. Total concentration of PM₁₀-associated PAHs reached 492.4 ng m⁻³ in winter and 26.0 ng m⁻³ in summer times. The multiple regression analysis was performed to predict total PM_2.5- and PM₁₀-associated PAHs and benzo(a)pyrene-equivalent (BaPE) concentrations with respect to meteorological parameters and particulate mass concentrations with the determination coefficients (R²) of 0.811, 0.805 and 0.778, respectively. The measured mean values of concentrations of total PM_2.5- and PM₁₀-associated PAHs were found to be 88.4 ng m⁻³ and 93.7 ng m⁻³ while their predicted mean values were found to be 92.5 ng m⁻³ and 98.2 ng m⁻³, respectively. In addition, observed and predicted mean concentration values of PM_2.5-BaPE were found to be 14.1 ng m⁻³ and 14.6 ng m⁻³. The close annual mean concentrations of measured and predicted total particulate related PAHs imply that the models can be reliably used for future predictions of particulate related PAHs in urban atmospheres especially where fossil fuels are mainly used for heating.     

Research on PM_2.5 Concentration Prediction Algorithm Based on Temporal and Spatial Features

PM_2.5 has a non-negligible impact on visibility and air quality as an important component of haze and can affect cloud formation and rainfall and thus change the climate, and it is an evaluation indicator of air pollution level. Achieving PM_2.5 concentration prediction based on relevant historical data mining can effectively improve air pollution forecasting ability and guide air pollution prevention and control. The past methods neglected the impact caused by PM_2.5 flow between cities when analyzing the impact of inter-city PM_2.5 concentrations, making it difficult to further improve the prediction accuracy. However, factors including geographical information such as altitude and distance and meteorological information such as wind speed and wind direction affect the flow of PM_2.5 between cities, leading to the change of PM_2.5 concentration in cities. So a PM_2.5 directed flow graph is constructed in this paper. Geographic and meteorological data is introduced into the graph structure to simulate the spatial PM_2.5 flow transmission relationship between cities. The introduction of meteorological factors like wind direction depicts the unequal flow relationship of PM_2.5 between cities. Based on this, a PM_2.5 concentration prediction method integrating spatial-temporal factors is proposed in this paper. A spatial feature extraction method based on weight aggregation graph attention network (WGAT) is proposed to extract the spatial correlation features of PM_2.5 in the flow graph, and a multi-step PM_2.5 prediction method based on attention gate control loop unit (AGRU) is proposed. The PM_2.5 concentration prediction model WGAT-AGRU with fused spatiotemporal features is constructed by combining the two methods to achieve multi-step PM_2.5 concentration prediction. Finally, accuracy and validity experiments are conducted on the KnowAir dataset, and the results show that the WGAT-AGRU model proposed in the paper has good performance in terms of prediction accuracy and validates the effectiveness of the model.     

Spatial distribution of particulate matter (PM10 and PM2.5) in Seoul Metropolitan Subway stations

The aims of this study are to examine the concentrations of PM10 and PM2.5 in areas within the Seoul Metropolitan Subway network and to provide fundamental data in order to protect respiratory health of subway workers and passengers from air pollutants. A total of 22 subway stations located on lines 1-4 were selected based on subway official's guidance. At these stations both subway worker areas (station offices, rest areas, ticket offices and driver compartments) and passengers areas (station precincts, subway carriages and platforms) were the sites used for measuring the levels of PM. The mean concentrations of PM10 and PM2.5 were relatively higher on platforms, inside subway carriages and in driver compartments than in the other areas monitored. The levels of PM10 and PM2.5 for station precincts and platforms exceeded the 24-h acceptable threshold limits of 150 microg/m3 for PM10 and 35 microg/m3 for PM2.5, which are regulated by the U.S. Environmental Protection Agency (EPA). However, levels measured in station and ticket offices fell below the respective threshold. The mean PM10 and PM2.5 concentrations on platforms located underground were significantly higher than those at ground level (p<0.05).     

A New Model Using Multiple Feature Clustering and Neural Networks for Forecasting Hourly PM2.5 Concentrations,and Its Applications in China

Particulate matter with an aerodynamic diameter no greater than 2.5 μm (PM_2.5) concentration forecasting is desirable for air pollution early warning. This study proposes an improved hybrid model, named multi-feature clustering decomposition (MCD)–echo state network (ESN)–particle swarm optimization (PSO), for multi-step PM_2.5 concentration forecasting. The proposed model includes decomposition and optimized forecasting components. In the decomposition component, an MCD method consisting of rough sets attribute reduction (RSAR), k-means clustering (KC), and the empirical wavelet transform (EWT) is proposed for feature selection and data classification. Within the MCD, the RSAR algorithm is adopted to select significant air pollutant variables, which are then clustered by the KC algorithm. The clustered results of the PM_2.5 concentration series are decomposed into several sublayers by the EWT algorithm. In the optimized forecasting component, an ESN-based predictor is built for each decomposed sublayer to complete the multi-step forecasting computation. The PSO algorithm is utilized to optimize the initial parameters of the ESN-based predictor. Real PM_2.5 concentration data from four cities located in different zones in China are utilized to verify the effectiveness of the proposed model. The experimental results indicate that the proposed forecasting model is suitable for the multi-step high-precision forecasting of PM_2.5 concentrations and has better performance than the benchmark models.     

High-pressure crystallization of poly(lactic acid) with and without N2 atmosphere protection

High-pressure crystallization experiments of poly(lactic acid) (PLA) were conducted under air and N₂ atmosphere. Compared with the sharp decrease of the molecular weight of air sample from 1.63 × 10⁵ to 3.11 × 10⁴, the weight loss of N₂ protection sample was successfully restricted to the value below 10 %. Stable α-crystals were generated in both air and N₂ protection samples which both exhibited very high crystallinity up to 66.3 and 64.5 %, respectively. It is high pressure that leads to the perfect crystalline structure by inducing crystalline reorganization and lamellar thickening. A diffraction streak appeared in the 2D-SAXS pattern of air sample in contrast to the broad scattering signal in N₂ protection sample, implying the formation of oriented crystals during PLA degradation. As observed from scanning electron microscopy, the spherulite size of air sample was larger than that of N₂ protection sample, for the radius growth rate of PLA crystals increased as molecular weight decreased. Accordingly, N₂ atmosphere protection can not only effectively prevent PLA from degradation, but also acquire highly crystallized PLA.