Simulation of Wind Circulation and Pollutant Diffusion Over the Pearl River Delta Region

Changes in urban surface areas and population growth have significantly affected the weather and environment. Emissions of nitrogen oxides are increasing in the Pearl River Delta region. Nitrogen compounds emitted by factories and motor vehicles are the major sources of nitric pollution. To study the impacts of urbanization and the relationship between pollutant diffusion and the atmospheric environment, the nonhydrostatic mesoscale forecast model MM5 (v3.73), which was developed by Penn State University and the National Center of Atmospheric Research, and a mass continuity equation for air pollutants, were used in this study. Two experiments were designed. One experiment (BE) applied horizontal grid resolutions of 27, 9, 3, and 1?km in four nested domains. The other experiment adopted new land-use data (in domain 4) directly retrieved from Landsat Thematic Mapper imagery to replace the 1980s data of the United States Geological Survey in BE. A 48-h simulation (from 0000?UTC on 21 October to 0000?UTC on 23 October 2008) was conducted, with the first 12?h being the spin-up time and the remaining 36?h being the effective simulation, so as to capture the diurnal features of the thermally induced winds associated with the land–sea breeze and urban heat island circulations. The different results obtained from the two tests for wind circulation and air pollution dispersion and transportation in the Pearl River Delta region were analyzed. The simulated results show that the both experiments can well simulate land–sea breeze circulation and remarkable land–sea breeze evolution, comparing with observation data. The height of the PBL had a significant diurnal cycle. The structure of the wind field can obviously impact the dispersion of the NO _x in three dimensions. Nitrogen oxides mainly diffused along the dominant wind direction (east or southeast wind), therefore the majority of the pollutants accumulated in the northwest region of the fine domain in both simulation experiments. However, it induced the pollutants concentration in an irregular pattern due to the fine-resolution grid spaces and complicated inland wind field in the northwest area of the inner domain. Moreover, increasing the proportion of urban surface caused sensible heat flux increase, latent heat flux decrease and humility reducing relatively in the region of urban surface characteristics apparently. Urbanization will cause pollution accumulated severely over the urban surface.     

Assessment of the impact of the meteorological meso-scale circulation on air quality in arid subtropical region

In this paper, COSMO numerical weather prediction model is used to simulate land-sea breeze circulation in the north coast of Oman and to analyze the variability of the PBL depth. Typical summer day 1st August 2009 and winter day 1st January 2009 were simulated and verified by surface observations. The COSMO model was initialized using the German global model which runs as 40 km resolution and 40 vertical layers. The simulations show differences in the onset, strength, and inland penetration of the sea breeze. The high sea-land thermal contrast in the summer season induces earlier onset and progression of the sea breeze with larger horizontal and vertical extents. The summer and winter inland penetration is simulated around 150 and 65 km, respectively. The PBL depth was defined from the verticals profiles of the turbulence kinetic energy (TKE). The simulated PBL height varied at 1,600 m in summer and 700 m in the winter case. These results are in general in good agreement with the simulations of the National Centers for Environmental Prediction Global Data Assimilation System (NCEP-GDAS) model. The dispersive ability of the atmosphere was tested through the vertical mixing coefficient (VMC) generated by NCEP-GDAS simulations. The VMC during the summer simulated case is approximately four times larger than the respective one during the winter case. Consequently, during the advection of winter sea breeze, a shallow dome less than 100 m is shaped and forms an obstacle to the air-pollutant dispersion.     

厦门市气候特征变化与酸雨形成研究

对地面风场的研究表明，厦门存在局地和海陆风环流，自1955年以来年平均风速、混合层厚度均呈现下降趋势，大气污染物的水平和垂直扩散能力也呈下降趋势。降水酸度随海拔高度的变化情况表明，海陆风环流有利于酸性污染物的积累，且锋面降水过程中的光化学污染加重了降水的酸化程度。     

Multipoint source method in air pollution modelling of cold start emission

The paper presents a new method of air pollution modelling on a micro scale. For estimation of concentration of car exhaust pollutants, each car is treated as an instantaneous moving emission source. This approach enables us to model time and spatial changes of emission, especially during cold and cool start of an engine. These stages of engine work are a source of significant pollution concentration in urban areas. In this work, two models are proposed: one for the estimation of emission after cold start of the engine and another for the prediction of pollutant concentration. The first model (defined for individual exhaust gas pollutants) enables us to calculate the emission as a function of time after the cold or cool start, ambient temperature and average speed of motion. This model uses the HBEFA database. The second mathematical model is developed in order to calculate the pollutant dispersion and concentrations. The finite volume method is applied to discretise the set of partial differential equations describing wind flow and pollutant dispersion in the domain considered. Models presented in this paper can be called short-term models on a small spatial scale. The results of numerical simulation of pollutant emission and dispersion are also presented.     

Air pollution exposure monitoring and estimation. Part VI. Ambient exposure of adults in an industrialised region

This paper presents methodology and results of a dynamic individual air pollution exposure model (DINEX) that calculates the hourly exposure for each adult in a panel study. Each of over 260 participants, through the use of a diary, provided information used in the model to calculate his/her personal, individualised exposure. The participants filled out the diary daily, hour by hour, over two, two month periods. The exposure assessment model coupled the diary information and results of an indoor/outdoor measurement program, with the results of dispersion modelling on an hourly basis for an industrial area in Norway. The estimated air pollution concentrations from the dispersion model, based on continuous meteorological measurements, were calibrated with air pollutant concentrations measured continuously.     

An air quality balance index estimating the total amount of air pollutants at ground level

A new index named Air Quality Balance Index (AQBI), which is able to characterise the amount of pollution level in a selected area, is proposed. This index is a function of the ratios between pollutant concentration values and their standards; it aims at identifying all situations in which there is a possible environmental risk even when several pollutants are below their limit values but air quality is reduced. AQBI is evaluated by using a high-resolution three-dimensional dispersion model: the air concentration for each substance is computed starting from detailed emissions sources: point, line and area emissions hourly modulated. This model is driven with accurate meteorological data from ground stations and remote sensing systems providing vertical profiles of temperature and wind; these data are integrated with wind and temperature profiles at higher altitudes obtained by a Local Area Model. The outputs of the dispersion model are compared with pollutant concentrations provided by measuring stations, in order to recalibrate emission data. A three-dimensional high resolution grid of AQBI data is evaluated for an industrial area close to Alessandria (Northern Italy), assessing air quality and environmental conditions. Performance of AQBI is compared with the Air Quality Index (AQI) developed by the U.S. Environmental Protection Agency. AQBI, computed taking into account all pollutants, is able to point out situations not evidenced by AQI, based on a preset limited number of substances; therefore, AQBI is a good tool for evaluating the air quality either in urban and in industrial areas. The AQBI values at ground level, in selected points, are in agreement with in situ observations.     

Numerical simulation on pollutant dispersion from vehicle exhaust in street configurations

The impact of the street configurations on pollutants dispersion from vehicles exhausts within urban canyons was numerically investigated using a computational fluid dynamics (CFD) model. Three-dimensional flow and dispersion of gaseous pollutants were modeled using standard kappa - epsilon turbulence model, which was numerically solved based on Reynolds-averaged Navier-Stokes equations by the commercial CFD code FLUENT. The concentration fields in the urban canyons were examined in three cases of street configurations: (1) a regular-shaped intersection, (2) a T-shaped intersection and (3) a Skew-shaped crossing intersection. Vehicle emissions were simulated as double line sources along the street. The numerical model was validated against wind tunnel results in order to optimize the turbulence model. Numerical predictions agreed reasonably well with wind tunnel results. The results obtained indicate that the mean horizontal velocity was very small in the center near the lower region of street canyon. The lowest turbulent kinetic energy was found at the separation and reattachment points associated with the corner of the down part of the upwind and downwind buildings in the street canyon. The pollutant concentration at the upwind side in the regular-shaped street intersection was higher than that in the T-shaped and Skew-shaped street intersections. Moreover, the results reveal that the street intersections are important factors to predict the flow patterns and pollutant dispersion in street canyon.     

Filtering effect of wind flow turbulence on atmospheric pollutant dispersion

This paper presents a model for coupling the statistics of wind velocity distribution and atmospheric pollutant dispersion. The effect of wind velocity distribution is modeled as a three-dimensional finite-impulse response (3D-FIR) filter. A phase space representation of the 3D-FIR filter window is discussed. The resulting pollutant dispersion is the multiplication in the phase space of the 3-D Fourier transform of the pollutant concentration and the volume described by the filter window coefficients. The shape of the filter window in the phase space enables representing such effects as vortex shedding thermal currents, etc. The impact of spatial distribution of the sensors on the resulting pollutant spatial distribution and the 3-D FIR filter model employed also discuss. The case of a neutrally buoyant plume emitted from an elevated point source in a turbulent boundary layer considers. The results show that wind turbulence is an important factor in the pollutant dispersion and introduces expected random fluctuations in pollutant distribution and leads to spreading the distribution due to wind mixing.     

A model for the maximum credible hourly impact on any ground receptor from point sources with momentumdominated plume rise

A pollutant dispersion model is developed, allowing rapid evaluation of the maximum credible one-hour-average concentration on any given ground-level receptor, along with the corresponding critical meteorological conditions (wind speed and stability class) for stacks with momentum-dominated plume rise in urban or rural areas under buoyancy or no buoyancy induced dispersion. Site-specific meteorological data are not required, as the computed concentrations are maximized against all credible combinations of wind speed, stability class, and mixing height.The analysis is based on the dispersion relations of Pasquill-Gifford and Briggs for rural and urban settings respectively, the buoyancy induced dispersion correlation of Pasquill, the wind profile exponent values suggested by Irwin, the momentum plume rise relations of Briggs, as well as the Benkley and Schulman's model for the minimum mixing heights.The model is particularly suited for air pollution management studies, as it allows fast screening of the maximum impact on any selected receptor and evaluation of the ways to have this impact reduced. Also, for regulatory purposes, as it allows accurate setting of minimum stack height requirements as function of the exit gas volume and velocity, the pollutant emission rates and their hourly concentration standards, as well as the source location relative to sensitive receptors.     

Simulating the production and dispersion of environmental pollutants in aerosol phase in an urban area of great historical and cultural value

Mathematical models were developed to simulate the production and dispersion of aerosol phase atmospheric pollutants which are the main cause of the deterioration of monuments of great historical and cultural value. This work focuses on Particulate Matter (PM) considered the primary cause of monument darkening. Road traffic is the greatest contributor to PM in urban areas. Specific emission and dispersion models were used to study typical urban configurations. The area selected for this study was the city of Florence, a suitable test bench considering the magnitude of architectural heritage together with the remarkable effect of the PM pollution from road traffic. The COPERT model, to calculate emissions, and the street canyon model coupled with the CALINE model, to simulate pollutant dispersion, were used. The PM concentrations estimated by the models were compared to actual PM concentration measurements, as well as related to the trend of some meteorological variables. The results obtained may be defined as very encouraging even the models correlated poorly: the estimated concentration trends as daily averages moderately reproduce the same trends of the measured values.     

A Numerical Study of Airflow and Pollutant Dispersion Inside an Urban Street Canyon Containing an Elevated Expressway

The goal of this study is to investigate numerically the wind flow and pollutant dispersion within an urban street canyon containing an elevated expressway and reveal the impacts of elevated expressway on the atmospheric environment in the canyon. A two-dimensional numerical model for simulating airflow and pollutant dispersion inside urban street canyons is first developed based on the Reynolds-averaged Navier–Stokes equations coupled with the standard k???ε turbulence model and the convection–diffusion equation for passive species transport, and then it is validated against a wind tunnel experiment. It was found that the model-predicted results agree well with the experimental data. Having established this, the wind fields and pollutant distributions in the canyon containing an elevated expressway are evaluated. The numerical results show that the expressway height above the street floor and the gap distance between the expressway and the building wall have considerable influence on airflow and pollutant level inside a canyon: (1) the vortical flow structure in the canyon varies with the expressway height for a constant gap distance, under certain expressway heights, only one main clockwise vortex is formed, while under others one main vortex as well as one or two secondary vortices above and below the expressway are created; (2) the pollutant level within the canyon increases when an expressway is placed in the canyon, especially when the expressway height equals the building height the flow velocities in the canyon are drastically reduced and air exchange in and above the canyon is seriously impeded by the expressway, which leads to a much higher pollution level in the canyon; and (3) the wider gap distance is favorable to pollutant removal from the canyon.     

Estimation of Ozone Trend in Central Greece, Based on Meteorologically Adjusted Time Series

Data referring to an approximately 8-year period (1999–2007) are analyzed in order to estimate the trend of the daily maximum hourly value of ozone concentration at the east coast of central Greece, where the summer background ozone concentration is high. A Kolmogorov–Zurbenko filter is applied to remove the short-term component from the raw time series of ozone and meteorological variables. Regression models are developed in order to produce meteorologically adjusted ozone time series, involving the noise-free temperature, relative humidity, and wind speed as independent variables. The analysis verifies that the meteorological adjustment provides better results on estimating ozone’s trend, which is found to be increasing (α?=?0.001) with an annual rate of 1.34?±?0.07?μg/m³. This trend could mainly be attributed to policy and changes in the emissions of ozone’s precursors. Additionally, the short-term component of ozone concentration is also meteorologically adjusted and its impact on the trend is examined. The analysis shows that its contribution is of minor importance when the ozone trend is adjusted by temperature, relative humidity, and wind speed. Moreover, the sea breeze circulation system that is frequently developed in the area influences the short-term and seasonal ozone variation, and therefore, it should be taken into account when producing meteorologically adjusted time series. The study’s conclusions could be exploited by environmental and agricultural authorities in order to develop their long-term strategies towards the air quality management.     

Seasonal variations of air pollutant concentrations within Krasnoyarsk City

This paper examines the significant differences in seasonal variations of criteria pollutant concentrations in various parts of a large urban area. These differences are caused by the microclimatic heterogeneity of the city and show the influence of breeze and orographic-type circulations on urban air pollution. The temperature heterogeneity of Krasnoyarsk territory during the winter leads to an increase of 150% in CO air pollution levels in the central part of city. During the summer the orographical heterogeneity of Krasnoyarsk City leads to increases of up to 400% in air pollution for different areas.     

NARX神经网络模型在昆明市环境空气质量预测中的应用

神经网络模型作为一种重要的手段被广泛应用于数学计算、物理建模、水文模拟、环境预测、人工智能等研究领域。为验证神经网络模型在高原山地城市环境空气质量预测中的作用,以昆明市环境空气自动监测站气象因子和污染物浓度数据为基础,构建NARX神经网络模型,对污染物浓度进行预测。结果表明,基于NARX神经网络建立的预测模型具有很强的非线性动态描述能力,能够对环境空气6参数做出较为准确的预测,其预测浓度相对误差显著低于CMAQ、NAQPMS空气质量数值模式以及LSTM统计模型预测结果。优化后的NARX神经网络对污染物浓度变化趋势的预测较其他几个模式更为敏感。     

Modelling of Fluid Flow and Pollutant Dispersion in a Street Canyon

A two-dimensional steady state numerical simulation has been carried out for a typical street canyon ventilated by a cross-wind. The PHOENICS package from CHAM was used to solve for the air flow above and within the street canyon. The k-epsilon turbulence model was used for turbulence modelling and pollutant sources were added at ground level over the road but not over the pavements. Results for the air flow showed the formation of a longitudinal vortex within the street canyon, as found by other researchers. Pollutant concentrations were predicted with the highest values occurring at the leeward walls of the upwind buildings, and the lowest values on the windward walls of the downwind buildings. The accuracy of these simulations was examined by comparing the predicted results with field observations. Reasonable agreement was obtained, confirming the difference between concentrations on the leeward and windward walls. The results show that the dispersion characteristics can be simulated in terms of structural configurations.     

Simulation of the migration and transformation of petroleum pollutants in the soils of the Loess plateau: a case study in the Maling oil field of northwestern China

We developed a coupled water–oil simulation model to simulate the migration and transformation of petroleum-derived contaminants in the soil of the Xifeng oil field. To do so, we used the HYDRUS-2D model, which simulates the diffusion, adsorption or desorption, and microbial degradation of petroleum-derived hydrocarbons in the soil–water system. The saturated soil hydraulic conductivity of petroleum-derived pollutants was 0.05 cm?day^?1, which is about 1 to 2 % of the soil moisture permeability coefficient. Our numerical simulation results show that spilled crude oil was mainly concentrated in the surface horizons of the soil. The organic pollutant concentration tended to be highest nearest to the pollution source. The pollutant migration was generally concentrated within the top 20 to 30 cm of the soil, with the maximum concentration in the top 5 cm of the soil. With passing time, the pollutant accumulation increased and the adsorption and degradation functions reached a dynamic balance with the input rate at depths greater than 30 cm below the soil surface. The oil-derived pollutants totaled 50 to 100 mg?kg^?1 under the dynamic balance condition, which occurred after 20 to 30 years. The petroleum-derived pollutant concentration in the loess soil was inversely correlated with the horizontal distance from the oil well, and the concentration decreased greatly at a distance greater than 40 m from the well.     

长株潭区域一次重度污染过程气象成因

利用PM_2.5质量浓度、地面气象要素、NCEP、ERSST＿V3、GBL等资料，研究了2021年12月7—11日长株潭地区一次重度空气污染过程的特征及成因。结果表明，高空平直环流、无明显槽脊影响，地面弱冷空气活跃是本次重度空气污染过程的主要环流形势特征；地面均压场、小风和升温增湿是此次重度空气污染过程的主要气象要素特征。污染物浓度变化与主导风向和污染通道密切相关，本地风速对混合层的高度、污染物水平扩散影响较大，600～700 hPa逆温层有利于污染物在主导风作用下近距离传输及在低层交换积累。我国中东部污染物积聚是长株潭区域重要的污染来源，长株潭地区存在区域性同步污染现象。低层流入长株潭区域气流轨迹差异及地理条件是长株潭污染物空间分布差异的重要因素。     

Numerical Simulations on the Effect of Sea–Land Breezes on Atmospheric Haze over the Pearl River Delta Region

The atmospheric haze over the Pearl River Delta (PRD) was investigated by using the Models-3 Community Multi-scale Air Quality modeling system with meteorological fields simulated by the Fifth-generation National Center for Atmospheric Research/Penn State University Mesoscale Model (MM5) from September 26th to September 30th, 2004. The model-simulated meteorological elements and particulate matter with aerodynamic diameter less than 10 μm (PM₁₀) were compared with observations at four air quality-monitoring stations. The results showed that MM5 successfully reproduced the diurnal variations of temperature, wind speed, and wind directions at these stations. The temporal variations of the simulated values were consistent with those of the observed (such as temperature, wind speed, and wind direction). The correlation coefficient was 0.91 for temperature and 0.56 for wind speed. The modeling results show that the spatial distributions of simulated PM₁₀ were closely related to the source emissions indicating three maxima of PM₁₀ over the PRD. The sea–land breezes diurnal cycle played a significant role in the redistribution and transport of PM₁₀. Nighttime land breeze could transport PM₁₀ to the coast and the sea, while daytime sea breeze (SB) could carry the accumulated PM₁₀ offshore back to the inland cities. PM₁₀ could also be transported vertically to a height of up to about 1000 m because of strong turbulence in the SB front. Process analyses indicated that the emission sources and the vertical diffusion were the major processes to influence the concentrations of particulate matter with aerodynamic diameter less than 2.5 μm (PM_2.5).     

佛山市近地面臭氧污染特征及相关气象因子分析

利用2014年佛山市8个国控大气自动监测点位的O_3监测数据,分析了佛山市的O_3污染特征,结果表明,2014年O_3日最大8 h平均值的第90百分位数为167μg/m~3,O_3为首要污染物的超标天数为43d,占比46.7%;ρ(O_3)区域变化不大;ρ(O_3)月变化呈现"三峰型",全年高ρ(O_3)集中在6—10月份,其中7月份出现全年最高峰值;ρ(O_3)日变化呈单峰型分布,夜间浓度较低且变化平缓,14:00—16:00左右达到峰值,并存在一定的"周末效应",但并不明显;ρ(O_3)与气温呈显著正相关,与湿度、气压、雨量呈显著负相关,与风向、风速的相关性相对较弱;总体上看,高温、低湿、微风、偏南风、低压、无雨的天气条件下高ρ(O_3)更容易出现。     

Nonpoint Source Pollution Assessment of Wujiang RiverWatershed in Guizhou Province,SW China

The amount of pollution from nonpoint sources flowing in the streams of the Wujiang River watershed in Guizhou Province, SW China, is estimated by a geographic information system (GIS)-based method using rainfall, surface runoff and land use data. A grid of cells of 100 m in size is laid over the landscape. For each cell, mean annual surface runoff is estimated from rainfall and percent land use, and expected pollutant concentration is estimated from land use. The product of surface runoff and concentration gives expected pollutant loading from that cell. These loadings are accumulated going downstream to give the expected annual pollutant loadings in streams and rivers. By dividing these accumulated loadings by the similarly accumulated mean annual surface runoff, the expected pollutant concentration from nonpoint sources is determined for each location in a stream or river. Observed pollutant concentrations in the watershed are averaged at each sample point and compared to the expected concentrations at the same locations determined from the grid cell model. In general, annual nonpoint source nutrient loadings in the Wujiang River watershed are seen to be predominantly from the agricultural and meadow areas. The total annual loadings through the outlet of the watershed are 40,309 and 2,607 tons for total nitrogen (TN) and total phosphorus (TP), respectively.