Diffusion Of Air Pollutants Research Articles

Synergetic Power-Gas Flow With Space-Time Diffusion Control of Air Pollutants Using a Convex Multi-Objective Optimization

Accurate and effective control mode of pollutant emissions is the key to alleviate the environmental impacts of energy supply systems. For this purpose, this paper establishes a precise space-time diffusion (STD) model of air pollutants associated with emission sources and atmosphere environment factors, and proposes a novel STD control of air pollutant emissions. Compared to the traditional emission quantity control, the proposed STD control takes the air pollutant diffusion and space-varying environmental protection demands into account, which can truly reduce the harm of air pollutant emissions. In view of an increasing interdependence between power system and natural gas system, a novel multi-objective optimal power-gas flow (MOPGF) with STD control of air pollutants is constructed. To solve the MOPGF with conflicting objectives and nonconvex gas transmission constraints, a generalized membership optimization (GMO) incorporating penalty convex-concave procedure (PCCP) based convexification is developed. GMO aims to coordinate conflicting objectives and PCCP convexifies the nonconvex gas dynamics, such that a high-quality solution can be obtained. Finally, simulations are carried out to verify the effectiveness of the STD control to reduce the influence of generation emissions, and the superiority of the convex multi-objective optimization for the MOPGF.

Using Multiple Linear Regression Method to Evaluate the Impact of Meteorological Conditions and Control Measures on Air Quality in Beijing During APEC 2014

Meteorological conditions have important impact on the diffusion and transport of air pollutants, thus separating and quantifying the impact of meteorological factors is a prerequisite for evaluation of air pollution control measures. Using observation data on SO2, NO, NO2, NOx, CO, PM2.5, PM1, and PM10 as well as meteorological factors at the Chaoyang site, an urban site in Beijing, we evaluated the impact of meteorological conditions and control measures on air quality in Beijing during APEC 2014 (from 15 October to 30 November, 2014) by the multiple linear regression method. The simulation performance of a multivariate linear regression model based on the parameters of meteorological factors for predicting pollutant concentration assuming constant emission conditions were ideal, produced a range of determination coefficient (R2) of 0.494-0.783. Our results suggested that air pollution control measures reduced the concentration of SO2, NO, NO2, NOx, CO, PM2.5, PM1, and PM10 by 48.3%, 53.5%, 18.7%, 40.6%, 3.6%, 34.8%, 28.8%, and 40.6%, while meteorological conditions reduced the concentration of SO2, NO, NO2, NOx, CO, PM2.5, PM1, and PM10 by 1.7%, -2.8%, 18.7%, 4.5%, 18.6%, 27.5%, 30.6%, and 35.6%. The combination of meteorological factors and control measures has significantly improved the air quality in Beijing during the APEC period. Control measures played a leading role in the reduction of SO2 and nitrogen oxides, and meteorological factors played a leading role in the reduction of CO. Meteorological factors and control measures made roughly equal contributions to the reduction of particulate matter. We also used the relative weight method to study the contribution of meteorological factors to the pollutant concentration. The results showed that the decisive meteorological factors on the concentrations of different pollutants were different.

Grey Mathematics Model for Atmospheric Pollution Based on Numerical Simulation

Urban air environment is a complex system with multiple objectives, multi levels and multiple factors. In this paper, the grey analysis of atmospheric environmental system is carried out, and the grey differential equation of air pollution is established, and the calculation method analysis and model verification of the grey numerical model are carried out. The relationship between the model parameters and the numerical solution is mainly analyzed, and the concentration field of the pollutant diffusion in the unsteady state is plotted. In this paper, the atmospheric environment system is analyzed from the grey system theory, and a more objective grey mathematical model is set up to carry out the Grey Numerical Simulation of the air pollution diffusion in urban area. It is of great practical significance to the flexible management and decision of air pollution control.

Dynamic Surveillance System for Contamination Accidents in Chemical Industry Park Based on Internet of Things

In recent years, the frequently occurring contamination accidents in the chemical industry parks in China has posed great threats to the healthy development of the national economy and social stability. For this purpose, this paper conceives a set of dynamic surveillance system against such accidents, which, on the premise of rapidity, simplicity, and reliability principles, revamps and redesign the HYSPLIT air pollution model for the interface, architecture, and functions, wholly integrates with air pollution diffusion model, numerical meteorology forecasting model, and the Geographic Information System (GIS). With the business operation mode, this system can effectively warn against the “uncertainty” of atmospheric pollution events in the chemical industry park, timely access the information about whether any pollutant exceeds allowable limits when an accident occurs. In the response to the emergency accident, it enables quantitative analysis and visual expression on chemical pollutant concentration limits, development trends and health risks, so as to provide an effective business and information support for decision commanders.

Comparison of mixing layer height inversion algorithms using lidar and a pollution case study in Baoding, China

Beijing–Tianjin–Hebei area is suffering from atmospheric pollution from a long time. The understanding of the air pollution mechanism is of great importance for officials to design strategies for the environmental governance. Mixing layer height (MLH) is a key factor influencing the diffusion of air pollutants. It plays an important role on the evolution of heavy pollution events. Light detection and ranging (lidar), is an effective remote-sensing tool, which can retrieve high spatial and temporal evolution process within mixing layer (ML), especially the variation of MLH. There are many methods to retrieve MLH, but each method has its own applicable limitations. The Mie-lidar data in Beijing was firstly used to compare three different algorithms which are widely used under different pollution levels. We find that the multi-layer structure near surface may cause errors in the detection of mixing layer. The MLH retrieved based on image edge detection was better than another two methods especially under heavy polluted episode. Then we applied this method to investigate the evolution of the mixing layer height during a pollution episode in December 2016. MLH at Gucheng county showed the positive correlation with the concentration of particulate matters during the start of this pollution episode. The elevated pollution level in Gucheng was not associated with MLH's decrease, and the significantly increased particulate matters raised the boundary layer, which trapped the pollutants near the surface.

The influence of terrestrial transport on visibility and aerosol properties over the coastal East China Sea

Air pollutants from East Asia continent can affect the physio-chemical and optical properties of marine aerosols under seasonal winds. We investigated the change of visibility and haze frequency from 1974 to 2017 over the coastal East China Sea (ECS), and reconstructed the light extinction coefficients according to the chemical compositions of PM2.5 samples collected at Huaniao Island in the ECS. The annual average visibility significantly decreased from over 25 km in the early 1970s to <18 km in recent 4 years. The occurrence of daily maximum haze frequency was approximately 3-h later with respect to land sites, which could be explained by the diffusion of air pollutants from nearby cities (haze peak around rush hour) to the coastal ECS as well as the formation of secondary aerosols enhanced by photochemical reactions around noon at the condition of affluent gaseous precursors. Meanwhile, anthropogenic chloride transported from the land could increase the concentration of Cl− in marine aerosol, which may weaken the Cl− depletion phenomenon over coastal ECS and even induced considerable Cl− enrichment during the severe haze event in Jan. 2013. The largest contributor to the light extinction was (NH4)2SO4 followed by NH4NO3 and OM in almost all seasons. Especially in winter and spring, (NH4)2SO4 accounted for 45% and 52% of total light extinction, respectively. The estimated bext was lower than the monitored values, suggesting that the contribution of some aerosol components (e.g. NH4Cl and large mode components) might be underestimated. Further study on the combination of observation and estimation of specific aerosol contribution to the visibility impairment are needed.

Stability control of air pollutant diffusion in Weakly Decaying Delayed States

At present, the air pollution problem in our country is prominent and the air pollution is getting more and more serious. Air pollution poses a great threat to the life and health of everyone and the development of the whole society and economy. In order to effectively carry out the air pollution control, we need to accurately grasp the air pollutants in the air diffusion and migration rules, the use of aerodynamic model of weak attenuation of air pollutant particles diffusion model was studied, the Gaussian Diffusion Model The basic structure, the method of parameter determination and the secondary development of GIS were studied deeply. The mathematical model of air pollutant diffusion was constructed by the close coupling method. Furthermore, the aerodynamic analysis of air pollutant particles diffusion under weak decay conditions is given, and the decay control of air pollutants under steady meteorological conditions that are unfavourable to diffusion is pointed out. After visualizing the diffusion results, it can directly and accurately grasp the influence range of pollutants, provide strong support for the research and governance of atmospheric pollution, and at the same time, provide a scientific basis for emergency treatment of sudden atmospheric pollution incidents.

Spatio-temporal variation of wind influence on distribution of fine particulate matter and its precursor gases

Frequent occurrence of severe haze in Beijing indicates the importance of effective decisions and clear goals to reduce the concentration of particulate matter in the atmosphere. To achieve this goal, elucidation of the elements governing fine particulate matter concentrations should be considered as one of the priorities. In this paper, we proposed a statistical model based on physical understanding of the diffusion of air pollutants by wind to investigate the sensitivity of fine particulate matter and its precursor gases concentrations to wind speed and direction. By using our method, it is possible to determine the major wind directions that have large impact on air quality for a particular area. Our results showed that the influence of wind on the concentration of particulate matter and its precursor gases varies spatially over Beijing. Our method suggested that both local emission sources of fine particulate matter and its precursor gas (NO2) and transported SO2 from regional industries should be reduced for the remediation of severe air pollution scenarios, especially in the Beijing urban area. Our approach serves as a good complement for commonly used approaches for source apportionment analysis without exploiting complicated methods. The method shows its feasibility in identifying air pollutant emission sources based on wind patterns and can be used in other regions as an aid in air pollution controlling programs.

Integrating CFD and GIS into the Development of Urban Ventilation Corridors: A Case Study in Changchun City, China

Given the situation of urban expansion and environmental deterioration, the government and researchers are paying considerable attention to ventilation corridors. The construction of urban ventilation corridors requires quantitative data support. Computational fluid dynamics (CFD) has advantages in the fine assessment of wind environment, and a geographic information system (GIS) has excellent performance in spatial analysis. With Changchun City used as an example, this study proposes the establishment of ventilation corridors on an urban scale to mitigate the urban-heat-island effect, and to accelerate the diffusion of air pollution. CFD simulations provided detailed spatiotemporal characteristics of wind speed and wind direction at various heights. These simulations were useful for identifying potential ventilation corridors. In general, the wind-speed and wind-direction characteristics at a height of 30 m clearly indicated potential ventilation corridors. Potential paths existed in the leading wind and south–north directions. The areas that required improvement were favorably situated in the path of potential ventilation corridors. The main roads, green spaces, and water had good connectivity. A total of five ventilation corridors were constructed, and they will directly affect the poor urban thermal environment, and enhance the mobility of air.

Seasonal statistical analysis of the impact of meteorological factors on fine particle pollution in China in 2013–2017

Based on long-term PM2.5 data observed at high temporal and spatial resolution, the relationships between PM2.5, primary emission, and weather factors in China during four seasons were examined using statistical analysis. The results reveal that primary emission plays a decisive role in the spatial distribution and seasonal variability of PM2.5, except in western China, where PM2.5 is controlled by dust weather. In addition to the accumulation of primary emissions, unfavorable meteorological conditions for the diffusion of air pollution lead to the occurrence of PM2.5 pollution. The significant dynamic factors affecting PM2.5 concentration are surface wind speed, planet boundary layer height, and ventilation coefficient, especially in winter. The ventilation coefficient is inversely correlated with PM2.5. Better ventilation is more favorable for the dilution and outflow of local PM2.5. However, in spring and autumn, ventilation coefficient and PM2.5 are positively correlated over the southern regions with low emission, indicating that ventilation also affects the inflow of PM2.5 from outside the region. Wind shear, 850 hPa divergence, and vertical velocity have insignificant effects on the long-term variations in PM2.5. The significant thermal factor is 850 hPa temperature in winter, except in the Pearl River Delta and Xinjiang regions. In spring, the influence of each thermal factor is weak. In summer, the influences of temperature and humidity are more significant than in spring. In autumn, the influence of humidity is relatively obvious, compared with other thermal factors. The correlation coefficients between multi-factors regressed and observed PM2.5 concentrations pass the 95% confidence test, and are higher than that of single-factor regression over most regions. The observed data from December 2016 to February 2017 were chosen to test the regression equation. The test result reveals that the regression equation is effective for predicting PM2.5 concentrations over regions with high primary emission.

The characteristics of abnormal wintertime pollution events in the Jing-Jin-Ji region and its relationships with meteorological factors

Despite the implementation of strict air pollution control measures in recent years, severe haze events were still encountered in the Beijing-Tianjin-Hebei (Jing-Jin-Ji) region during the winter 2016. In this work, seasonal differences in correlations between air pollution and geographic terrain, atmospheric dynamical and thermal structures, and PBL height over the Jing-Jin-Ji region in history and recent years were investigated and a comprehensive model of atmospheric factors affecting winter air pollution formation was proposed. We found that the distribution of PM2.5 concentration closely correlated with the topography feature of China and the difference in haze pollution intensity between winter and other seasons was the most significant in the Jing-Jin-Ji region. The “semi-enclosed” terrain along with the enhanced winter “downdraft” strongly inhibited the diffusion and convection of air pollutants in this region. Meanwhile, seasonal variations of the vertical thermal structure over the Jing-Jin-Ji region, i.e., the anomalous pattern of “upper warming and bottom cooling” structure in the middle troposphere, and the “weak wind zone” were more distinct in winter 2016 than historical record, providing an important precondition for the frequent occurrence of thermal inversion layers and severe pollution episodes in the lower troposphere. In addition, abnormally low PBL heights occurred in the Jing-Jin-Ji region during severe pollutant episodes in winter 2016, with mean postmeridian PBL height in December of only 869.4 m, the minimum value since 2013. PM2.5 concentration was not only closely related to PBL height but also the “warm cover” structure in the middle troposphere. The stronger the structure was, the lower the PBL height became, and severer the pollution event was encountered, accompanying water vapor accumulation and intensification of the thermal inversion layer in the lower troposphere. All above observations revealed the mutual feedback correlations between air pollutants concentration and meteorological factors.

Geospatial analysis of relationship between climate factors and diffusion of air pollution in Chiang Mai, Thailand

Geospatial analysis of relationship between climate factors and diffusion of air pollution in Chiang Mai, Thailand

气象条件与成都市空气质量的关系研究

利用2007~2016年成都市常规地面气象观测资料、探空资料以及2015~2016年空气质量指数监测资料，分析了成都市空气质量变化的特征，探讨了气象要素与空气质量之间的关系，结果表明：成都市空气质量以优良或轻度污染为主，空气污染冬季最重，夏季最轻。市内常年盛行偏北风，风速较小，静风频率高，对污染的扩散十分不利；当日降水量大于0.5mm时，对空气质量有明显的改善作用；空气质量还与气温、气压、能见度、日照等气象要素有显著的相关关系。因中性类天气条件出现频率较高，所以大气稳定度对空气质量作用具有不确定性，此时合适的逆温层高度和强度可以作为判定空气质量的重要依据。当逆温层高度低于933hpa，逆温强度大于2.2℃时，污染难以扩散。另外，显著的城市热岛效应有利于大气污染扩散，对改善市区空气质量有一定作用。 This paper studied the characteristics of air pollution of Chengdu and the relationship between air quality and meteorological condition by using the air quality index form 2015-2016 and normally ground meteorological data and sounding data from 2007-2016 of Wen Jiang station. The results show that good air quality or lightly polluted air primarily occurred in Chengdu and the serious air pollution usually occurs in winter; in summer, air pollution is the lightest. North wind is the prevailing wind, wind speed is low, and calm wind frequency is high. These are unfavorable for the pollution dispersion. It showed that when daily precipitation > 0.5 mm, the air quality will be improved evidently. Meanwhile, air quality of Chengdu is significantly correlated with temperature, pressure, visibility and sunshine duration. For neutral weather conditions occur frequently, atmospheric stability is nearly impossible to decide air quality, unless appearing coordinate with temperature inversion. When inversion height is lower than 933 hpa and the intensity of inversion > 2.2˚C, the air pollution is difficult to spread. What’s more, significant urban heat island effect is conducive to the diffusion of air pollution, which has a certain effect on improving air quality in urban areas.

Estimation of Ground PM2.5 Concentrations using a DEM-assisted Information Diffusion Algorithm: A Case Study in China

When estimating national PM2.5 concentrations, the results of traditional interpolation algorithms are unreliable due to a lack of monitoring sites and heterogeneous spatial distributions. PM2.5 spatial distribution is strongly correlated to elevation, and the information diffusion algorithm has been shown to be highly reliable when dealing with sparse data interpolation issues. Therefore, to overcome the disadvantages of traditional algorithms, we proposed a method combining elevation data with the information diffusion algorithm. Firstly, a digital elevation model (DEM) was used to segment the study area into multiple scales. Then, the information diffusion algorithm was applied in each region to estimate the ground PM2.5 concentration, which was compared with estimation results using the Ordinary Kriging and Inverse Distance Weighted algorithms. The results showed that: (1) reliable estimate at local area was obtained using the DEM-assisted information diffusion algorithm; (2) the information diffusion algorithm was more applicable for estimating daily average PM2.5 concentrations due to the advantage in noise data; (3) the information diffusion algorithm required less supplementary data and was suitable for simulating the diffusion of air pollutants. We still expect a new comprehensive model integrating more factors would be developed in the future to optimize the interpretation accuracy of short time observation data.

Regional severe particle pollution and its association with synoptic weather patterns in the Yangtze River Delta region, China

Abstract. Regional air pollution is significantly associated with dominant weather systems. In this study, the relationship between the particle pollution over the Yangtze River Delta (YRD) region and weather patterns is investigated. First, the pollution characteristics of particles in the YRD are studied using in situ monitoring data (PM2.5 and PM10) in 16 cities and Terra/MODIS AOD (aerosol optical depth) products collected from December 2013 to November 2014. The results show that the regional mean value of AOD is high in the YRD, with an annual mean value of 0.71±0.57. The annual mean particle concentrations in the cities of Jiangsu Province all exceed the national air quality standard. The pollution level is higher in inland areas, and the highest concentrations of PM2.5 and PM10 are 79 and 130 µg m−3, respectively, in Nanjing. The PM2.5 : PM10 ratios are typically high, thus indicating that PM2.5 is the overwhelmingly dominant particle pollutant in the YRD. The wintertime peak of particle concentrations is tightly linked to the increased emissions during the heating season as well as adverse meteorological conditions. Second, based on NCEP (National Center for Environmental Prediction) reanalysis data, synoptic weather classification is conducted and five typical synoptic patterns are objectively identified. Finally, the synthetic analysis of meteorological fields and backward trajectories are applied to further clarify how these patterns impact particle concentrations. It is demonstrated that air pollution is more or less influenced by high-pressure systems. The relative position of the YRD to the anti-cyclonic circulation exerts significant effects on the air quality of the YRD. The YRD is largely influenced by polluted air masses from the northern and the southern inland areas when it is located at the rear of the East Asian major trough. The significant downward motion of air masses results in stable weather conditions, thereby hindering the diffusion of air pollutants. Thus, this pattern is quite favorable for the accumulation of pollutants in the YRD, resulting in higher regional mean PM10 (116.5 ± 66.9 µg m−3), PM2.5 (75.9 ± 49.9 µg m−3), and AOD (0.74) values. Moreover, this pattern is also responsible for the occurrence of most large-scale regional PM2.5 (70.4 %) and PM10 (78.3 %) pollution episodes. High wind speed and clean marine air masses may also play important roles in the mitigation of pollution in the YRD. Especially when the clean marine air masses account for a large proportion of all trajectories (i.e., when the YRD is affected by the cyclonic system or oceanic circulation), the air in the YRD has a lesser chance of being polluted. The observed correlation between weather patterns and particle pollution can provide valuable insight into making decisions about pollution control and mitigation strategies.

Influences of wind and precipitation on different-sized particulate matter concentrations (PM2.5, PM10, PM2.5–10)

Though it is recognized that meteorology has a great impact on the diffusion, accumulation and transport of air pollutants, few studies have investigated the impacts on different-sized particulate matter concentrations. We conducted a systematic comparative analysis and used the framework of generalized additive models (GAMs) to explore the influences of critical meteorological parameters, wind and precipitation, on PM2.5, PM10 and PM2.5–10 concentrations in Wuhan during 2013–2016. Overall, results showed that the impacts of wind and precipitation on different-sized PM concentrations are significantly different. The fine PM concentrations decreased gradually with the increase of wind speed, while coarse PM concentrations would increase due to dust resuspension under strong wind. Wind direction exerts limited influence on coarse PM concentrations. Wind speed was linearly correlated with log-transformed PM2.5 concentrations, but nonlinearly correlated with log-transformed PM10 and PM2.5–10 concentrations. We also found the PM2.5 and PM2.5–10 concentrations decreased by nearly 60 and 15% when the wind speed was up to 6 m/s, respectively, indicating a stronger negative impact of wind-speed on fine PM than coarse PM. The scavenging efficiency of precipitation on PM2.5–10 was over twice as high as on PM2.5. Our findings may help to understand the impacts of meteorology on different PM concentrations as well as discriminate and forecast variation in particulate matter concentrations.

A review of air pollutant diffusion models for urban street

Street is an important place for urban residents, and the air quality in streets is closely related to residents' health. Air pollutant diffusion model is an often used measure to simulate and evaluate air quality in street canyon in recent years, but the problems existing in model application need to be clarified. This review selected four air pollutant diffusion models, i.e., ENVI-met, FLUENT, MISKAM and OSPM, which were most popular in street canyon studies. Through comparisons on the model mechanisms, the operational processes, the temporal-spatial resolutions and so on, their differences in model scopes and modeling capabilities in street canyon air quality simulation were discriminated, the model deficiencies were pointed out according to temporal scale, modeling, weather handling, turbulent simulation and photochemical pollution, and several model optimization measures were suggested in terms of street canyon study. Moreover, through reviewing the case stu-dies of the four models, the shortcomings in model application were concluded, and some new techniques were highlighted for future application studies such as laser radar to improve input data accuracy, and the importance of considering urban heat island and urban pollutant island simultaneously was emphasized in evaluating street environment quality.

Investigation of the absolute detection method of atmospheric temperature based on solid cavity scanning Fabry-Perot interferometer

measurement methods based on Rayleigh scattering are employed to relatively detect atmospheric temperature profiles. That is to say, the definition of response functions and calibration procedures is required for temperature retrieval. Because the thermal motion rate of gas molecule complies with Maxwell distribution, and gas molecule is always in motion state, the frequency of scattering return signal generates Doppler spectral broadening. There is a positive correlation between the full width at half maximum of widened Doppler spectrum and T1/2, atmospheric absolute temperature can be obtained by measuring the Doppler spectrum shape. In this paper, the fine detection method of the spectrum shape of Rayleigh scattering and residuary Mie-scattering correction method based on solid cavity scanning Fabry-Perot (F-P) interferometer are investigated. According to the characteristics of Rayleigh scattering spectrum, the free spectral range, the geometric length of solid cavity, the type of cavity media, the full width at half maximum, the reflectivity of cavity, and the scanning step are designed. When the electro-optical crystal of KD*P with the length of 8.5 mm acts as solid cavity medium of scanning F-P interferometer, the designed free spectral region and 3 dB bandwidth are 11.5 GHz and 60 MHz at the central wavelength of 354.7 nm, respectively. The energy datum of 185 discrete points at Rayleigh scattering spectrum are obtained by using an optimized solid cavity scanning F-P interferometer with the scanning voltage of 23.5 V. A fitting spectrum is generated by employing polynomial interpolation method at the atmospheric temperature of 300 K. The maximum absolute error and full width at half maximum error of Rayleigh scattering spectrum are 22 MHz and 337 kHz, respectively. In order to verify the results, a numerical simulation of Rayleigh scattering spectrum based on standard atmosphere model and S6 model is performed. The detection uncertainty of atmospheric temperature is up to 0.8 K. As SNR (signal to noise ratio) is 10, the detection distance is 4.5 and 7.9 km at day-time and night-time, respectively. The research provides a new solution of filter system for the achievement of all-time, high-precision, and absolute detection of atmospheric temperature in the future. In meteorology, in order to investigate the temporal and spatial characteristics, the change rules and physical mechanism of weather processes, the temperature in the boundary layer of urban atmosphere is absolutely detected, where human activities are frequent and the changes of weather elements are obviously at day and night. In addition, the absolute detection method of atmospheric temperature can provide the valid means to research urban heat island, weather forecast for urban environment, and high temperature alert. In environmental studies, the absolute detection of atmospheric temperature can provide the big amount of scientific data for establishment of numerical model and research on air pollution diffusion. There is reference significance for the investigation of filter system of similar lidar. Simultaneously, the scanning filter method provides a feasible solution for the filter system with the characteristics of miniaturization, high anti-interference and high stability in the space-based platform.

Progress in the impact of polluted meteorological conditions on the incidence of asthma.

It has been revealed by many studies that air pollution is one of the important inducements of asthma exacerbations. In addition, meteorological conditions such as high atmospheric pressure, low temperature, low humidity and large diurnal amplitude can directly induce asthma. Meanwhile, meteorological conditions play an important role in the diffusion, dilution and accumulation of air pollution. This article reviewed research progress in the impact of polluted meteorological conditions on the incidence of asthma.

Effect of urbanization on the urban meteorology and air pollution in Hangzhou

Urbanization has a substantial effect on urban meteorology. It can alter the atmospheric diffusion capability in urban areas and therefore affect pollutant concentrations. To study the effects of Hangzhou’s urban development in most recent decade on its urban meteorological characteristics and pollutant diffusion, 90 weather cases were simulated, covering 9 weather types, with the Nanjing University City Air Quality Prediction System and high-resolution surface-type data and urban construction data for 2000 and 2010. The results show that the most recent decade of urban development in Hangzhou substantially affected its urban meteorology. Specifically, the average urban wind speed decreased by 1.1 m s −1; the average intensity of the heat island increased by 0.5°C; and the average urban relative humidity decreased by 9.7%. Based on one case for each of the nine weather types, the impact of urbanization on air pollution diffusion was investigated, revealing that the changes in the meteorological environment decreased the urban atmosphere’s diffusion capability, and therefore increased urban pollutant concentrations. For instance, the urban nitrogen oxides concentration increased by 2.1 μg m −3 on average; the fine particulate matter (diameter of 2.5 μm or less; PM2.5) pollution concentration increased by 2.3 μg m −3 on average; in highly urbanized areas, the PM2.5 concentration increased by 30 μg m −3 and average visibility decreased by 0.2 km, with a maximum decrease of 1 km; the average number of daily hours of haze increased by 0.46 h; and the haze height lifted by 100–300 m. The “self-cleaning time” of pollutants increased by an average of 1.5 h.