Complex Meteorological Conditions Research Articles

Dynamic Optimization Method for Unmanned Ship Weather Route Based on Multi-stage Inverse Reasoning

Route is an important factor for safe and efficient navigation of ships. In this paper, unmanned ship navigation environment under complex marine meteorological conditions was analyzed. Wind, wave conditions were integrated considered. Dynamic optimization model of unmanned ship weather route was established, in which meteorological and hydrological information was considered, unfavorable influences of which on ship navigation were reduced, energy and sailing time were saved, and route was found. Simulation results showed that initial fixed weather route could be optimized, and the model could be applied to dynamic optimization of weather routes of unmanned ships in large areas under complex meteorological conditions.

Analysis of Accidents Resulting from the Interaction of Air and Ground Vehicles at Airports

The analysis of the causes and consequences of accidents resulting from the interaction of air and ground vehicles at airports is presented in this paper. The data on accidents involving the following aircrafts were taken into account: airplanes, helicopters and unmanned aircrafts; the ground vehicles included: fuel tankers, cars, snow plows, pushback tractors and other vehicles operating at the airport. As a basis for the analysis, data on eleven such accidents that occurred at the airports of a number of countries in the period from 2000 to 2021 were used. The analysis of what types of ground and aircrafts were involved in the accidents is made. When studying the main and associated causes of accidents, the actions of all participants in traffic control at the airport (operators of ground vehicles, aircraft pilots and air traffic control officers) were analyzed. In addition, the impact of complex meteorological conditions (snow, fog, heavy rain, etc.) limiting visibility was analyzed. The classification of accidents is carried out in accordance with the level of danger of their consequences. At the final stage, possible ways to reduce the risk of such events in the future are discussed.

Radiological consequence assessments using time-varying source terms in ONERS- decision support system for nuclear emergency response

Online Nuclear Emergency Response System (ONERS) is a Decision Support System (DSS) developed for the management of Off-Site Nuclear Emergencies for Nuclear Power Plant sites of India. In this work, ONERS is incorporated with a module ‘Time-Dependent Source term (TDS)' for real-time online plume dispersion and radiological consequence assessments using time-varying source terms which is likely during an accidental release. TDS facilitates online dispersion and dose calculations by initiating the FLEXPART particle dispersion model with WRF predicted real-time meteorological forecasts and inputs on hourly release rates of 25 significant radionuclides of both ground level and elevated releases for any reactor accident over a 72-h meteorological forecast domain. The TDS is tested against the existing uniform source term approach for a hypothetical accident for two types of frequent weather conditions over Kalpakkam nuclear site in southern India. Simulations for a complex weather condition (monsoon & local sea breeze) during 26–29 September 2019 indicate that though the simulated plume area is similar in both the cases, the area affected is different as governed by the meteorological condition during the period of releases. It is found that the area and direction of potentially affected zone is determined by most frequent wind flow in the case of uniform source term and the flow direction during the period of maximum release in the case of time-dependent source term. Simulations for winter weather condition during 10–13 January 2020 with nearly uniform flow indicate similar results in both uniform and time-varying release cases. Results indicate that while the time-dependent source terms provide more realistic projection of radiological impact under complex meteorological conditions over uniform source term, both approaches would nearly converge when the maximum release occurs under the most frequent windflow condition. The two approaches are complementary to each other for response actions given the requirements of rapid assessments with gross source terms in the initial phases and more refined assessments with detailed source terms in the later phases of emergencies.

Daily reference evapotranspiration prediction of Tieguanyin tea plants based on mathematical morphology clustering and improved generalized regression neural network

Tieguanyin tea plant is the most important tea cultivar in Fujian Province, China. It has suffered great economic losses due to high temperature and dry weather in recently years. This study proposed a prediction model for daily reference evapotranspiration (ET0) of Tieguanyin based on the combination of mathematical morphology clustering (MMC) and generalized regression neural networks (GRNN). Average air temperature, sunshine hours and relative humidity were chosen as the input factors of GRNN after a correlation analysis of the microclimate factors of the tea garden. The MMC was adopted to cluster the historical meteorological data to find the similar class as the training dataset of GRNN. The fruit fly optimization algorithm (FOA) was used to optimize the smoothing factor of GRNN. The meteorological data from JAN. 2018 to OCT. 2019 measured in Dabaofeng tea garden, Anxi County, Fujian Province, China were used to train and test the proposed model, and the performances was assessed with RMSE, MAE and model validity coefficient. The prediction results of different seasons show that the proposed model is efficient with high accuracy and has good adaptability under complex meteorological conditions.

Retrieving Volcanic Ash Top Height through Combined Polar Orbit Active and Geostationary Passive Remote Sensing Data

Taking advantage of both the polar orbit active remote sensing data (from the Cloud-Aerosol Lidar with Orthogonal Polarization—CALIOP) and vertical information and the geostationary passive remote sensing measurements (from the Spinning Enhanced Visible and Infrared Imager) with large coverage, a methodology is developed for retrieving the volcanic ash cloud top height (VTH) from combined CALIOP and Spinning Enhanced Visible and Infrared Imager (SEVIRI) data. This methodology is a deep-learning-based algorithm through hybrid use of Stacked Denoising AutoEncoder (SDA), the Genetic Algorithm (GA), and the Least Squares Support Vector Regression (LSSVR). A series of eruptions over Iceland’s Eyjafjallajökull volcano from April to May 2010 and the Puyehue-Cordón Caulle volcanic complex eruptions in Chilean Andes in June 2011 were selected as typical cases for independent validation of the VTH retrievals under various meteorological backgrounds. It is demonstrated that using the hybrid deep learning algorithm, the nonlinear relationship between satellite-based infrared (IR) radiance measurements and the VTH can be well established. The hybrid deep learning algorithm not only performs well under a relatively simple meteorological background but also is robust under more complex meteorological conditions. Adding atmospheric temperature vertical profile as additional information further improves the accuracy of VTH retrievals. The methodology and approaches can be applied to the measurements from the advanced imagers onboard the new generation of international geostationary (GEO) weather satellites for retrieving the VTH science product.

Evaluation of the Performance of Low-Cost Air Quality Sensors at a High Mountain Station with Complex Meteorological Conditions

Low-cost sensors have become an increasingly important supplement to air quality monitoring networks at the ground level, yet their performances have not been evaluated at high-elevation areas, where the weather conditions are complex and characterized by low air pressure, low temperatures, and high wind speed. To address this research gap, a seven-month-long inter-comparison campaign was carried out at Mt. Tai (1534 m a.s.l.) from 20 April to 30 November 2018, covering a wide range of air temperatures, relative humidities (RHs), and wind speeds. The performance of three commonly used sensors for carbon monoxide (CO), ozone (O3), and particulate matter (PM2.5) was evaluated against the reference instruments. Strong positive linear relationships between sensors and the reference data were found for CO (r = 0.83) and O3 (r = 0.79), while the PM2.5 sensor tended to overestimate PM2.5 under high RH conditions. When the data at RH >95% were removed, a strong non-linear relationship could be well fitted for PM2.5 between the sensor and reference data (r = 0.91). The impacts of temperature, RH, wind speed, and pressure on the sensor measurements were comprehensively assessed. Temperature showed a positive effect on the CO and O3 sensors, RH showed a positive effect on the PM sensor, and the influence of wind speed and air pressure on all three sensors was relatively minor. Two methods, namely a multiple linear regression model and a random forest model, were adopted to minimize the influence of meteorological factors on the sensor data. The multi-linear regression (MLR) model showed a better performance than the random forest (RF) model in correcting the sensors’ data, especially for O3 and PM2.5. Our results demonstrate the capability and potential of the low-cost sensors for the measurement of trace gases and aerosols at high mountain sites with complex weather conditions.

Concept of Microclimate in Russian Legislation

In the constantly changing conditions of the external environment, the microclimate is supported by the stabilizing systems of the building in the overall system ”building - exterior fences and engineering equipment”. To create a comfortable microclimate in the room, special systems are used: heating, ventilation, and humidification. To create thermal comfort indoors means ensuring its complex meteorological conditions in which the thermoregulatory system of the body is in a state of the least tension, and all the other physiological functions occur at the level most beneficial for the body. In the modern world the quality of the indoor environment is a priority, part of the requirements is reflected in the modern standards of green building, part in the national standards. So the Russian Federation has legislative and normative-legal acts, reflecting the characteristics of environmental quality: GOST (State Standard) 30494-2011, SanPiN (Sanitary Regulations and Norms) 2.1.2.1002-00, GOST R ISO (Russian National Standard) 7730-2009, SN 2605-82, SNiP (Construction Standards and Regulations) 23-05-95 and others. Normalized microclimatic indicators include temperature, humidity and air velocity, surface temperature of building envelopes, objects, equipment. But at the present stage, the formation of a harmonized and safe environment of the room depends on many factors, which should not only reflect functional, social, climatic, urban planning, construction design, architectural-artistic and economic characteristics, but also socio-psychological and environmental components of the room.

Environmental Economic Dispatch Strategy for Power-Gas Interconnection System Considering Spatiotemporal Diffusion of Air Pollutant and P2G in Coastal Areas

This paper proposes an environmental economic dispatch strategy for power-gas interconnection system considering spatiotemporal diffusion of air pollutant and P2G in coastal areas. Firstly, considering the complex and changeable meteorological conditions in coastal areas and the regional characteristics of the atmospheric layer, an air pollutant diffusion model considering the local sea-land circulation and thermal inner boundary layer is studied. Then, a multi-objective environmental economic dispatch model is employed, and the economic cost, carbon emission quantities, and pollutant concentration contribution values are set as optimization objectives. Finally, we conduct the optimization with the multi-objective distributed algorithm based on ADMM. Cases study is carried out on IEEE39 power network and Belgium 20 gas network, which validate the effectiveness of the proposed strategy.

Characteristics and source apportionment of PM2.5 on an island in Southeast China: Impact of sea-salt and monsoon

Abstract To study the combined effects of the East Asian monsoon and ocean emissions on wintertime and summertime PM2.5 in island cities, filter samples were collected simultaneously at four different functional sites. Based on the chemical compositions of PM2.5, and positive matrix factorization (PMF) model analysis, the pollution characteristics and sources were determined. Insignificant differences, and some correlation in PM2.5 reconstructed compositions were found among the sites (Pt-test > 0.05, P > .05), while significant differences, and no correlation, were found between winter and summer (PANOVA .05). There was more serious chloride depletion in summer (0.88 ± 0.05), caused by both significant Cl− depletion and Na+ enrichment, than in winter (0.18 ± 0.10). The concentrations of non-sea-salt-SO42− in winter were close to those in summer, but the sulfate oxidation ratio (SOR) in winter was much lower than that in summer. The results could be explained by the fact that sea-salt-SO42− has an important contribution to secondary inorganic aerosol on island cities. From both air trajectory clustering and PMF analysis, it was found that there was significant aerosol aging and regional transport in the island city during the East Asian monsoon, and that continental air masses control the variation of air pollution in winter, while sea breezes dominate the characteristics of PM2.5 in summer. This study helps to understand the characteristics and source mechanisms of PM2.5 pollution under complex meteorological conditions in island cities.

A WRF-Chem model-based future vehicle emission control policy simulation and assessment for the Beijing-Tianjin-Hebei region, China

Using 2025 as the target year, we quantitatively assessed the reduction potentials of emissions of primary pollutants (including CO, HC, NOx, PM2.5 and PM10) under different vehicle control policies and the impacts of vehicle emission control policies in the BTH region on the regional PM2.5 concentration in winter and the surface ozone (O3) concentration in summer. Comparing the different scenarios, we found that (1) vehicle control policies will bring significant reductions in the emissions of primary pollutants. Among the individual policies, upgrading new vehicle emission standards and fuel quality in Beijing, Tianjin, and Hebei will be the most effective policy, with emission reductions of primary pollutants of 26.3%–54.7%, 38.0%–70.3% and 46.0%–81.6% in 2025, respectively; (2) for PM2.5 in winter, the Combined Scenario (CS) will lead to a reduction of 0.5–3.9 μg m−3 (3.5%–11.6%) for the monthly average PM2.5 concentrations in most areas. The monthly nitrate and ammonium concentrations would reduce by 5.8% and 5.3%, respectively, in the whole BTH region, indicating that vehicle emission control policies may play an important role in the reduction of PM2.5 concentrations in winter, especially for nitrate aerosols; and (3) for O3 concentrations in summer, vehicle emission control policies will lead to significant decreases. Under the CS scenario, the maximum reduction of monthly average O3 concentrations in the summer is approximately 3.6 ppb (5.9%). Most areas in the BTH region have a decrease of 15 ppb (7.5%) in peak values compared to the base scenario. However, in some VOC-sensitive areas in the BTH region, such as the southern urban areas, significant reductions in NOx may lead to increases in ozone concentrations. Our results highlight that season- and location-specific vehicle emission control measures are needed to alleviate ambient PM2.5 and O3 pollution effectively in this region due to the complex meteorological conditions and atmospheric chemical reactions.

Performance prediction of the combined cycle power plant with inlet air heating under part load conditions

A combined cycle power plant with inlet air heating (CCPP-IAH) system is proposed to solve the problems of ice and humidity blockages in winter climate. The performance of the CCPP-IAH system under part load conditions is analyzed via both experimental and simulation methods. The application of the inlet air heating technology significantly improves the part load efficiency and enhances the operational safety of the combined cycle power plant under complex meteorological conditions. Results show that a higher inlet air temperature will contribute a lower gas turbine thermal efficiency for proposed system. However, the heated inlet air by the recovered energy in heat recovery steam generator raises efficiencies for both the heat recovery steam generator and the overall system. The fuel consumption drops by 0.02 kg/s and 0.03 kg/s under the power load of 65% and 80%, respectively. The inlet air humidity decrease to 30% under the heated inlet air temperature of 303 K. Moreover, the exergy destruction for both Brayton cycle part and Rankine cycle part decrease with the inlet air temperature increasing. The daily fossil fuel will raise up to 2.9 ton/day and to 5.1 ton/day under the power load of 65% and 80%, respectively. The annual economic benefit from energy saving is more than $ 5.88 × 105 and the payback period is less than 3 years.

МЕТОД ЗАГАЛЬНОГО ПРОЕКТУВАННЯ РЕГІОНАЛЬНИХ ПАСАЖИРСЬКИХ ЛІТАКІВ

A method of general design of regional passenger planes for transportation of passengers, baggage, mail and cargo on domestic and international airlines with the possibility of operating on airfields with concrete and prepared unpaved runways is proposed. Airplane is designed to replace the outdated Tu-134 passenger aircraft in the fleet of airlines of the CIS and other countries. The concept of creating an aircraft using integrated design systems has been developed. The effect of the aircraft parameters on the aerodynamic and mass characteristics was taken into account, subject to the requirements for layout and flight safety. The range of variation of the aircraft modifications parameters has been determined. The method has been tested by comparing the obtained parameters with the regional passenger aircraft of the Antonov State Enterprise.The aircraft features a modern aerodynamic configuration and efficient engines. Modern flight and navigation equipment and radio communication equipment, the use of multifunctional indicators, electrical distant flight control system allowing them to be used on any airways, in simple and complex meteorological conditions, day and night, and on routes with high flight intensity at high comfort level of passengers and crew.Passenger comfort is provided at the average level of long-haul aircraft, and is achieved by a rational layout and composition of service rooms, deep ergonomic optimization of the overall and individual space of the passenger compartment. The aircraft fully complies with the AP-25 airworthiness standards.The main technical characteristics of the aircraft are comparable to the characteristics of the analogue aircraft of Embraer and Bombardier companies. In addition, the aircraft has several advantages, such as the ability to operate on aerodromes with poorly prepared and unpaved runways, the presence of a door-ramp, high engine safety from damage by foreign objects, a high level of passenger comfort and large luggage racks, high efficiency of operation; high level of competitiveness in the global market

METHODOLOGY FOR ACCOUNTING THE INFLUENCE OF METEOROLOGICAL FACTORS ON THE EFFICIENCY OF APPLICATION OF UNMANNED AERIAL VEHICLES ON THE BASIS OF SYSTEM ANALYSIS

ObjectivesThe aim of the study is to increase the effectiveness of unmanned aerial vehicles (UAVs) in the context of destabilising meteorological factors on the basis of an identification of links and patterns of unmanned aerial vehicles operating in difficult weather conditions.MethodsIn this work, in order to account for the effect of meteorological factors on the effectiveness of unmanned aerial vehicles, the methods of system analysis, mathematical modelling of atmospheric phenomena and processes, as well as probability theory and statistical assessment, were applied.ResultAn analysis of open literature sources devoted to the issues of operation and practical application of unmanned aerial vehicles (UAVs) under the influence of environmental factors was carried out. A classification of destabilising influences (DI) affecting the performance of a UAV flight mission is developed and presented. The dynamic probabilistic indicator, which, in characterising the dynamics of UAV functions as a complex technical system is referred to as “time efficiency of the UAV flight mission”, is substantiated. A methodology for estimating the dynamic efficiency indicator of the UAV’s functionality during the performance of a flight mission (FM) underDI conditions is developed on the basisof a probabilistic model of the conflicting interaction between UAV and DI. Strategies for selecting the trajectories of flights around local zones in which UAVs can be influenced by DI are given. To estimate the DI intensity and determine the size of the local disturbance zone, a mathematical model is proposed, whose application makes it possible to improve the UAV functioning under complex meteorological conditions (CMC) by taking into account the information on the space-time variability of dangerous for UAV weather-related phenomena (DWP). In the process of constructing the UAV functioning model, the use of conflict theory methods permitted adequate models for the analysis and evaluation of the dynamic efficiency indicator of the UAV functioning during the performance of FM in DI conditions to be developed, as well as the patterns of meteorological factors influencing the effectiveness of the UAV application to be revealed.ConclusionThe methodology proposed in the article makes it possible to increase the effectiveness of unmanned aerial vehicles (UAVs) under complex meteorological conditions by a time index of 20-30% as compared with traditional approaches.

Investigating sources of variability and error in simulations of carbon dioxide in an urban region

As cities embark upon greenhouse gas (GHG) mitigation efforts, there is an increasing need for accurate quantification of urban emissions. In urban areas, transport and dispersion is particularly difficult to simulate using current mesoscale meteorological models due, in part, to added complexity from surface heterogeneity and fine spatial/temporal scales. It is generally assumed that the errors in GHG estimation methods in urban areas are dominated by errors in transport and dispersion. Other significant errors include, but are not limited to, those from assumed emissions magnitude and spatial distribution. To assess the predictability of simulated trace gas mole fractions in urban observing systems using a numerical weather prediction model, we employ an Eulerian model that combines traditional meteorological variables with multiple passive tracers of atmospheric carbon dioxide (CO2) from anthropogenic inventories and a biospheric model. The predictability of the Eulerian model is assessed by comparing simulated atmospheric CO2 mole fractions to observations from four in situ tower sites (three urban and one rural) in the Washington DC/Baltimore, MD area for February 2016. Four different gridded fossil fuel emissions inventories along with a biospheric flux model are used to create an ensemble of simulated atmospheric CO2 observations within the model. These ensembles help to evaluate whether the modeled observations are impacted more by the underlying emissions or transport. The spread of modeled observations using the four emission fields indicates the model's ability to distinguish between the different inventories under various meteorological conditions. Overall, the Eulerian model performs well; simulated and observed average CO2 mole fractions agree within 1% when averaged at the three urban sites across the month. However, there can be differences greater than 10% at any given hour, which are attributed to complex meteorological conditions rather than differences in the inventories themselves. On average, the mean absolute error of the simulated compared to actual observations is generally twice as large as the standard deviation of the modeled mole fractions across the four emission inventories. This result supports the assumption, in urban domains, that the predicted mole fraction error relative to observations is dominated by errors in model meteorology rather than errors in the underlying fluxes in winter months. As such, minimizing errors associated with atmospheric transport and dispersion may help improve the performance of GHG estimation models more so than improving flux priors in the winter months. We also find that the errors associated with atmospheric transport in urban domains are not restricted to certain times of day. This suggests that atmospheric inversions should use CO2 observations that have been filtered using meteorological observations rather than assuming that meteorological modeling is most accurate at certain times of day (such as using only mid-afternoon observations).

Correlation and scaling behaviors of fine particulate matter (PM2.5) concentration in China

Air pollution has become a major issue and caused widespread environmental and health problems. Aerosols or particulate matters are an important component of the atmosphere and can transport under complex meteorological conditions. Based on the data of PM2.5 observations, we develop a network approach to study and quantify their spreading and diffusion patterns. We calculate cross-correlation functions of the time lag between sites within different seasons. The probability distribution of correlation changes with season. It is found that the probability distributions in four seasons can be scaled into one scaling function with averages and standard deviations of correlation. This seasonal scaling behavior indicates that there is the same mechanism behind correlations of PM2.5 concentration in different seasons. Further, the weighted degrees reveal the strongest correlations of PM2.5 concentration in winter and in the North China Plain for the positive correlation pattern that is mainly caused by the transport of PM2.5. These directional degrees show net influences of PM2.5 along Gobi and inner Mongolia, the North China Plain, Central China, and Yangtze River Delta. The negative correlation pattern could be related to the large-scale atmospheric waves.

Improved technical characteristics of the MI-8/17 in the army of FYR Macedonia

Worldwide experience has shown that MI-8/17 helicopters are on the top of the middle class list of high performance multipurpose helicopters, flying at high altitudes in complex meteorological conditions. The paper addresses their development, transport, as well as rescuing and combat capabilities. The excellent technical characteristics of flight and their capabilities for uninterrupted and smooth performance of tasks demonstrate the reason why the Armed forces of the FYR of Macedonia decided to use Mi-8/17 helicopters and are determined to invest in their modernization and improvement of their technical capabilities. The modernization of the resources of armies is a continuous process, which is a part of all modern military security structures. Most armed forces do not economize the funds allocated for this purpose, due to the fact that they aspire to achieve the planned capabilities, so that they would attain the ultimate preparedness in terms of capabilities of the security forces regarding technology and trained personnel.

Evaluation of Corona Loss in 750 kV Four-Circuit Transmission Lines on the Same Tower Considering Complex Meteorological Conditions

As an important index for measuring the operational economy of EHV AC transmission lines, corona loss (CL) is one of important factors worth considering during the operation and design of transmission lines. The 750-kV transmission lines are mainly distributed in high-altitude areas in northwestern China, where sand storm occurs frequently in spring and autumn. At present, a few researches are available on the evaluation of CL in multi-circuit transmission lines on the same tower in sandy and dusty area at high altitudes. Based on a transmission project with four-circuit transmission lines on the same tower in the north of Xi’an, Shaanxi Province, China, the electric field distributions of bundle conductors under two types of arrangement structure, including six and four cross-arms tower, were investigated. Then, by using the CL equivalent theory, the CL under meteorological conditions of fair, rainy, snowy, foggy, and dusty weather were evaluated. Finally, the optimal phase-sequence arrangement under the optimal tower modes was proposed, and the CL and resistance loss under the selected arrangements were compared.

Modern meteorological observations for aviation purposes

The purpose of this article. Meteorological support for aviation is a component of the safety systems. With the development of aviation technology, the requirements for it are growing. Today, aviation remains the most demanding user of meteorological information. The main parameters that affect the aircraft’s aerodynamic characteristics include air temperature, wind direction, atmospheric pressure, the height of the lower cloud boundary, the amount of precipitation and the frequency of dangerous meteorological phenomena. The aim of the study is a spatio-temporal analysis of meteorological parameters at the air base Chuguiv, Kharkiv region. Main material. Time series of daily average, average monthly air temperature, relative humidity, cloudiness, atmospheric pressure, atmospheric precipitation, wind direction and frequency of dangerous meteorological phenomena for the period 2008-2017 were processed as initial data. Changes in meteorological values during the year, season and month were studied. Favorable weather conditions for flights have been determined. Recommendations are developed regarding the performance of flights under various weather conditions. To date, many different aircraft flight models have been developed in non-standard weather situations. In T.V.Safonova’s work the forecast of the indicators of airports functioning and flights on routes in difficult meteorological conditions is considered. Consequently, aviation must have timely meteorological information increasing the safety, regularity and economy of flights for effective implementation of practical tasks. Conclusions. Analysis of the literature has showed that complex meteorological conditions create critical situations on routes and require further detailed study. To maintain a high level of meteorological service for aviation that meets international standards, it is necessary to conduct scientific and applied research in the field of aviation climatology and improve existing methods of aviation forecasting.

Assessment of regional influence from a petrochemical complex by modeling and fingerprint analysis of volatile organic compounds (VOCs)

This study aimed to demonstrate a strategy to investigate the influence of volatile organic compounds (VOCs) on its neighboring districts from a gigantic petrochemical complex. Monitoring of the VOCs in the region was achieved by a nine-station network, dubbed photochemical assessment measurement stations (PAMS), which produced speciated mixing ratios of 54 non-methane hydrocarbons (NMHCs) to represent VOCs with an hourly resolution within a 20 km radius. One-year (2013/10/1–2014/9/30) worth of PAMS data from the network were used in forms of total NMHCs (called PAMS-TNMHC) and speciated mixing ratios. Three dimensional modeling coupled with PAMS measurements successfully elucidated how the study domain was affected by the petrochemical complex and distant sources under three typical seasonal wind patterns: northeast monsoonal, southwest monsoonal, and local-circulation.More exquisite analysis of influence on the neighboring districts was permitted with the use of speciated mixing ratios of VOCs provided by the PAMS network. The ratios of ethylene/acetylene (E/A) > 3 and propylene/acetylene (P/A) > 1.5 were used as indicators to reveal the PAMS sites affected by the petrochemical emissions. Consequently, the hourly speciated data from the nine PAMS sites enabled a finer assessment of the districts affected by the complex to calculate the percent time of influence (dubbed TI%) for all the sites (districts). It was found that the region was more affected by the complex under both the northeast monsoonal and the local-circulation wind types with some of the PAMS sites greater than 5% for the TI%. By contrast, influence on the region was found minimal under the southwest monsoonal flow with the TI% small than 1.5% across all sites.This study successfully devised a method of assessment with the use of speciated measurements of selected VOCs and modeling to assess the influence of a prominent source on the neighboring districts by filtering out irrelevant sources under the complex meteorological conditions.

The impacts of roadside vegetation barriers on the dispersion of gaseous traffic pollution in urban street canyons

Vegetation barriers have been widely applied along urban streets to improve roadside air quality. For a deep investigation of their influences, field measurements and numerical simulations are performed in this study. Carbon monoxide (CO) is selected as a representative of gaseous traffic emissions for both field observations and numerical models. Computational Fluid Dynamics (CFD) models of the standard k-ε turbulent model and Eulerian approach for species transport are solved by FLUENT solver. Results obtained from numerical simulations show a good agreement with field observations on the distribution of roadside CO. In perpendicular wind conditions, both field observations and numerical simulations present a prominent CO reduction over the slow lanes (footpath and bikeway) when vegetation barriers exist. To effectively mitigate roadside air pollution, numerical simulations also provide the optimal heights for roadside vegetation barriers in the given street canyons. For street canyons with an aspect ratio (the ratio of building height to street width) ranging from 0.3 to 1.67, 1.1m can be used as an optimal height, and 2.0m could serve as an alternative if tall vegetation barriers are considered. For street canyons with an aspect ratio of lower than 0.3, 0.9m to 2.5m can be considered as the optimal heights for roadside vegetation barriers. According to sensitivity analysis, the optimal heights for vegetation barriers are largely insensitive to wind velocities in the given street canyons. In the more complicated urban street canyons and complex meteorological conditions, the optimal heights can be determined by specific numerical simulations. These findings are expected to provide important insights into alleviation of gaseous mobile emissions in terms of vegetation barrier design in urban streets.