Distribution Of Atmospheric Pollutants Research Articles

A Multi-UAV cooperative mission planning method based on SA-WOA algorithm for three-dimensional space atmospheric environment detection

Abstract In the application of rotorcraft atmospheric environment detection, to reflect the distribution of atmospheric pollutants more realistically and completely, the sampling points must be spread throughout the entire three-dimensional space, and the cooperation of multiple unmanned aerial vehicles (multi-UAVs) can ensure real-time performance and increase operational efficiency. In view of the problem of coordinated detection by multi-UAVs, the region division and global coverage path planning of the stereo space to be detected are studied. A whale optimization algorithm based on the simulated annealing-whale optimization algorithm (SA-WOA) is proposed, which introduces adaptive weights with the Levy flight mechanism, improves the metropolis criterion, and introduces an adaptive tempering mechanism in the SA stage. Path smoothing is subsequently performed with the help of nonuniform rational B-spline (NURBS) curves. The comparison of algorithms using the eil76 dataset shows that the path length planned by the SA-WOA algorithm in this paper is 10.15% shorter than that of the WOA algorithm, 13.25% shorter than the SA planning result, and only 0.95% difference from the optimal path length in the dataset. From the perspective of planning time, its speed is similar to WOA, with a relative speed increase of 27.15% compared to SA, proving that the algorithm proposed in this paper has good planning performance. A hardware system platform is designed and built, and environmental gas measurement experiments were conducted. The experimental results indicate that the multi-UAV collaborative environment detection task planning method proposed in this paper has certain practical value in the field of atmospheric environment detection.

Research on Automatic Wavelength Calibration of Passive DOAS Observations Based on Sequence Matching Method

Passive differential optical absorption spectroscopy (DOAS) is widely used to monitor the three-dimensional distribution of atmospheric pollutants. However, the observational and retrieval accuracy of this technique is significantly influenced by the precise wavelength calibration of solar spectra. Current calibration methods face challenges in automation when dealing with complex remote-sensing conditions. We introduce a novel automatic wavelength calibration algorithm for passive DOAS based on sequence-matching technology to estimate the spectral parameters of the spectrometer channels, integrating advanced processing measures such as feature structure enhancement and sub-pixel interpolation. These measures significantly reduce the dependency on reference spectrum resolution and accurately correct even minor spectral shifts. We perform sensitivity experiments using synthetic spectra to determine optimal retrieval configurations, followed by field tests at four cities on the Yangtze River Delta, China, to calibrate and compare passive DOAS instruments of various resolutions. Comparative verification in these field studies demonstrated that our algorithm was suitable for rapid spectral calibration within a wider resolution range of 0.03 nm to 0.1 nm with a wavelength inversion error < 0.01 nm. This highlights the applicability and calibration precision of our algorithm.

First retrieval of daily 160 m aerosol optical depth over urban areas using Gaofen-1/6 synergistic observations: Algorithm development and validation

The satellite-based aerosol optical depth (AOD), which can provide continuous spatial observations of aerosol loadings, is widely adopted to estimate atmospheric environmental quality and evaluate its risk for human health. However, current satellite-retrieved AOD products characterized by a comparatively coarse spatial resolution (≥1 km) can hardly analyze the structure of atmospheric pollution or its correlation with urban landscapes over populated urban areas. Existed studies have tried to address this deficiency by retrieving high-resolution AOD using Landsat images, whose long revisit period (16 days nominally), however, largely limits its applications related to urban air pollution research. To achieve both high spatial resolution and expected revisit period from satellite observation, in this study, a comprehensive AOD retrieval framework is developed for Wide-Field-of-View (WFV) satellite sensors to yield a daily AOD dataset over urban areas with 160 m spatial resolution, based on the Gaofen-1 and Gaofen-6 synergistic observations. To address the crucial challenge that the high spatial resolution and complex urban landscape both contribute a dramatic variation of land surface bidirectional reflectance, a Simulated-Annealing-coupled Semiempirical Modified Rahman-Pinty-Verstraete (SAS-MRPV) scheme is proposed to model and estimate the land surface reflectance (LSR) in the AOD retrieval framework, where the SAS-MRPV scheme is implemented using simulated annealing iteration initialized by the bidirectional reflectance distribution function (BRDF) products from the Moderate Resolution Imaging Spectrometer (MODIS) as a priori knowledge. The validation results demonstrate that the Gaofen WFV AOD retrievals exhibit good agreement with the ground-based AErosol RObotic NETwork (AERONET) and SONET (Sun-sky radiometer Observation NETwork) AOD, demonstrating the correlation coefficient and the expected error (EE)±(0.05 + 0.15AODAERONET/SONET) ratio respectively reaching up to 0.97 and over 80 %, and only slight bias fluctuations are found under different land cover types, aerosol loading, and seasonal conditions. Moreover, the validation results of Gaofen WFV AOD retrievals, with LSR estimated based on the SAS-MRPV scheme, the MODIS BRDF Products, and the Minimum Reflectance Technique (MRT) method, demonstrate better accuracy and completeness of AOD retrievals using the SAS-MPRV scheme over both natural and impervious land surfaces, indicating the stability and reliability of proposed SAS-MRPV LSR determination scheme in WFV AOD retrieval. In addition to that, the error analyses and quality control results demonstrate that the SAS-MRPV scheme is effective and necessary to guarantee the reliability and accuracy of land surface bidirectional reflectance estimation by identifying and excluding the land surface pixels unsuitable for LSR modeling, which mitigates the uncertainty and yield better accuracy in the final WFV AOD products. Furthermore, the inter-comparison between WFV-derived AOD against the operational MODIS Deep Blue (10 km), Dark Target (3 km), and Multi-Angle Implementation of Atmospheric Correction (MAIAC, 1 km) AOD products demonstrates that the 160 m WFV AOD retrievals, on the basis of obtaining similar aerosol overall descriptions as MODIS AOD retrievals, possess the capability to characterize the spatial distribution of atmospheric pollution at a finer scale with smoother variation under both clean and polluted conditions. With outstanding accuracy and reliable performance, the developed comprehensive high-resolution AOD retrieval framework exhibits substantial potential for operational AOD retrieval of Gaofen WFV satellite observations, which could be directly applied to other urban areas supporting further studies related to air pollution emission management and health risk assessment at extra-fine spatial scale.

Composition and size distribution of wintertime inorganic aerosols at ground and alpine regions of northwest China

Water-soluble inorganic ions (WSIIs) play a pivotal role in atmospheric chemical reactions, particularly influencing the formation of secondary particulate matter. A comprehensive grasp of the vertical distribution of atmospheric pollutants holds immense significance in understanding the diffusion and transportation of these pollutants. This study investigates the WSIIs of PM2.5 and size-segregated particles at the top (∼2060 m a.s.l.) and foot of Mt. Hua during the winter of 2020. All the measured ions present significant higher concentrations (1.9∼6.9 times) at the foot than the top. Cl− and K+ at the foot are more than 4 times of those at the top, whereas Ca2+ and Mg2+ are only 1.3–1.9 times higher. The particle size distribution of NO3−, SO42−, K+ and Cl− demonstrate a single peak distribution (0.7–1.1 µm) at the foot, but with a bimodal distribution (0.7–1.1 µm and 4.7–5.8 µm) at the top. These differences suggest that the aerosol at the alpine region is mainly transported via long-distance from Northwest/North China, but limited influenced by vertical transport through valley breeze. The changes of concentration and size distribution of WSIIs in dust event and non-dust period indicate that the effects of dust event on aerosols at ground surface were weaker than that of the free troposphere of Guanzhong Plain. Notably, our study underscores the dominant influence of NO3− in shaping the gas-particle distribution of ammonia within the winter free troposphere. Our results highlight the significant role of long-range transport on aerosols in the free troposphere in Guanzhong Plain, Northwest China.

Distribution of Atmospheric Pollution in Southern Benin

Distribution of Atmospheric Pollution in Southern Benin

Measurement of the vertical distributions of atmospheric pollutants using an uncrewed aerial vehicle platform in Xi'an, China.

Vertical observations of atmospheric pollutants play crucial roles in a comprehensive understanding of the distribution characteristics and transport of atmospheric pollutants. A hexacopter uncrewed aerial vehicle equipped with miniature monitors was employed to measure the vertical distribution of atmospheric pollutants within a height of 1000 m at a rural site in Xi'an, China, in 2021. The concentrations of carbon monoxide (CO) and particulate matter (PM) showed generally decreasing trends with increasing height. The ozone (O3) concentration showed a general increasing trend with height followed by a gradual decreasing trend. Vertical decrements of PM2.5 and CO from 0 to 1000 m were significantly (p < 0.05) lower on observation days during summer (14.0 ± 8.1 μg m-3 and 8.7 ± 6.6 ppb, respectively), compared with those in winter (78.3 ± 14.1 μg m-3 and 34.8 ± 17.3 ppb, respectively). The horizontal transport of PM and CO mostly occurred in the morning and at night during winter observations at an altitude of 400-500 m. During the winter haze, the PM and CO profile concentrations below 500 m increased substantially with the decrease in the height of the thermal inversion layer. Vertical O3 transportation was observed in the afternoon and evening during summer, and a ∼37.7% (11.6 ppb) increase in ground-level O3 was observed in relation to vertical transport from the upper atmosphere. The results provide insights into the vertical distribution and transport of atmospheric pollutants in rural areas near cities.

Modeling and Predicting the Environment State in the Impact Area of a Copper–Nickel Plant: A Balanced Model of the Transformations of Atmospheric Deposition at the Catchment and in Lake

The paper discusses modeling the dynamics of nickel concentration in soils, water, and the bottom sediments of lakes caused by atmospheric emissions from the Pechenganickel plant, Kola Peninsula, throughout its whole operation period. The applied technology of balanced identification makes it possible to use a mathematical description of heterogeneous geochemical processes in ecosystems to combine heterogeneous experimental data and build up a computer model with an optimal balance of its complexity and fitting quality of the data. The model is used to analyze the spatial and temporal variability of natural objects in the zone of distribution of atmospheric pollution (nickel) from the Pechenganickel plant. The paper presents and discusses results of this study, including estimates of the retrospective state of the simulated objects (before the start of the intense studies) and a forecast of their dynamics until 2030. According to the model calculations, the intensity of Ni accumulation in the soil and bottom sediments was 2.35 and 4.48 mg/(m2 year) during the maximum deposition periods (1980–2005), whereas the model predicts a decrease in the intensity of Ni accumulation in the bottom sediments (0.23 mg/(m2 year)) and slow Ni leaching from the soil (0.19 mg/(m2 year)) after the shutdown of the plant.

Emission Inventory of Airborne Pollutants from Biomass Combustion in Guizhou Province

With the objective to ascertain the emissions of biomass combustion in Guizhou, the activity levels were measured through data collection and field surveys, and the emission factors were acquired using actual monitoring data and data cited from previous literature. A 3 km×3 km-gridded emission inventory of nine air pollutants from biomass combustion sources in Guizhou Province in 2019 was developed in combination with GIS technology. The results showed that the total emissions of CO, NOx, SO2, NH3, VOCs, PM2.5, PM10, BC, and OC in Guizhou were estimated to be 293505.53, 14781.19, 4146.11, 8501.07, 45025.70, 39463.58, 41879.31, 6832.33, and 15134.74 t, respectively. The distribution of atmospheric pollutants emitted by biomass combustion sources in different cities was noticeably uneven, being mainly concentrated in Qiandongnan Miao and Dong Autonomous Prefecture. The analysis of variation characteristics of emissions indicated that the monthly emissions were concentrated in February, March, April, and December, and the hourly emissions peaked daily from 14:00 to 15:00. Some uncertainty remained in the emission inventory. It is necessary to perform in-depth analyses of the accuracy of obtaining activity-level data, localize the emission factors through more combustion experiments in subsequent research for improving the emission inventory of air pollutants from biomass combustion in Guizhou Province, and provide a basis for the cooperative governance of the atmospheric environment.

ИССЛЕДОВАНИЕ ПРОЦЕССА ПРОВЕТРИВАНИЯ КАРЬЕРА ПРИ ВАРИАЦИИ УГЛА ОТКОСА БОРТА И ПАРАМЕТРА ФОНОВОЙ СТРАТИФИКАЦИИ НА БАЗЕ МЕТОДА ЧИСЛЕННОГО МОДЕЛИРОВАНИЯ

The results of the study are presented on the basis of the method of numerical modeling of the process of natural ventilation of the open pit during blasting operations with variations of two factors: natural ‒ the parameter of background stratification and technological ‒ the angle of slope of the side of the open pit. Numerical experiments were performed on the basis of a modified two-dimensional computer model of the microclimate of an open pit in a non-specialized COMSOL program code. Quantitative indicators of the influence of an increase in the inversion state of the atmosphere on an increase in the level of pollution and, accordingly, the time of natural ventilation, as well as a decrease in the asymmetry in the spatial distribution of atmospheric pollution of the open pit were obtained. Based on the analysis of the structure and quantitative indicators of velocity fields, it was shown that a decrease in the slope angle of the side of the open pit with a recirculating ventilation scheme leads to an increase in the time of natural ventilation

A Coverage Sampling Path Planning Method Suitable for UAV 3D Space Atmospheric Environment Detection

Air pollution affects people’s life and health, and controlling air pollution requires the collection of polluting gas information. Unmanned aerial vehicles (UAVs) have been used for environmental detection due to their characteristics. However, the limitation of onboard energy sources of UAVs will limit the coverage of the detection area and the number of gas samples collected, which will affect the assessment of pollution levels. In addition, to truly and completely reflect the distribution of atmospheric pollutants, it is necessary to sample the entire three-dimensional space. This paper proposes a three-dimensional space path planning method suitable for UAV atmospheric environment detection, which can generate a full-coverage path with optimal coverage density under energy constraints. Simulation results show that the proposed method can effectively improve the coverage density compared with other path generation methods. Field experiments show that the proposed method is reliable and accurate in the application of UAV atmospheric environment space detection.

Temporal and Spatial Distribution Analysis of Atmospheric Pollutants in Chengdu-Chongqing Twin-City Economic Circle.

In order to study the temporal and spatial distribution characteristics of atmospheric pollutants in cities (districts and counties) in the Chengdu–Chongqing Twin-city Economic Circle (CCEC) and to provide a theoretical basis for atmospheric pollution prevention and control, this paper combined Ambient Air Quality Standards (AAQS) and WHO Global Air Quality Guidelines (GAQG) to evaluate atmospheric pollution and used spatial correlation to determine key pollution areas. The results showed that the distribution of atmospheric pollutants in CCEC presents a certain law, which was consistent with the air pollution transmission channels. Except for particulate matter with an aerodynamic diameter equal to or less than 2.5 μm (PM2.5) and ozone (O3), other pollutants reached Grade II of AAQS in 2020, among which particulate matter with an aerodynamic diameter equal to or less than 10 μm (PM10), PM2.5, sulfur dioxide (SO2), nitrogen dioxide (NO2) and carbon monoxide (CO) have improved. Compared with the air quality guidelines given in the GAQG, PM10, PM2.5, NO2 and O3 have certain effects on human health. The spatial aggregation of PM10 and PM2.5 decreased year by year, while the spatial aggregation of O3 increased with the change in time, and the distribution of NO2 pollution had no obvious aggregation. Comprehensive analysis showed that the pollution problems of particulate matter, NO2 and O3 in CCEC need to be further controlled.

Spatiotemporal Distribution of Atmospheric Pollutants and Its Relationship with Vegetation Index in the Major Grain-Producing Areas of China

Spatiotemporal Distribution of Atmospheric Pollutants and Its Relationship with Vegetation Index in the Major Grain-Producing Areas of China

Ten-year emission characteristics of atmospheric pollutants from incineration of sacrificial offerings in China

The incineration of sacrificial offerings is a significant widely practiced custom that is also a kind of neglected air pollution source in China. Our results showed that the emission factors of particulate matter, SO2, CO, NOx, and VOCs emitted from the incineration of sacrificial offerings with purification systems were reduced by 95%, 19%, 9%, 82%, and 42%, respectively, compared with those without a purification system, revealing a significant effect of the flue gas purification system on reducing particulate matter and gaseous pollutants. The emission level of air pollutants from the incineration of sacrificial offerings remained stable before 2013 and then showed a remarkable decrease after the implementation of China´s Air Pollution Prevention Action Plan in 2013. The emissions of TSP (total suspended particulate), PM10, PM2.5, and NOx in 2009 were 8222, 6106, 5656 and 15,878 ton, respectively, obviously higher than 3434, 2551, 2305 and 8579 ton in 2019. Such trend was affected by both the quantity of incineration and the installation rate of purification systems after the Emission Standard of Air Pollutants for Crematory (GB 13801-2015) issued in China. Distinct spatial distribution of atmospheric pollutants from incineration of sacrificial offerings was found with higher in the east and south of China than the west and north of China, which is proportional to the regional economy and population. The maximum ground-level concentration typically occurred at 0.12-0.2 km from the pollution source, posing potential health risks to people entering and exiting funeral and burial sites and nearby residents.

Spatiotemporal Variations and Influent Factors of Tropospheric Ozone Concentration over China Based on OMI Data

Spatiotemporal distribution of atmospheric pollutants has been a hot topic in the field of environmental science in recent years. Rapid economic development, urbanization, and industrialization have resulted in a significant increase in ozone emissions, and China is facing the issue of air pollution with high ozone concentrations in the ambient air. The Aura ozone monitoring instrument (OMI), can provide long-term and large-scale dynamic monitoring of tropospheric column ozone (TCO). The TCO concentrations over China were extracted and analyzed from 2005 to 2019. The results showed that the spatiotemporal distribution of ozone concentration decreased from northeast to southeast in China. The seasonal variations of ozone concentration were spring’s concentration is greater than winter’s concentration, winter’s concentration is greater than summer’s concentration, summer’s concentration is greater than autumn’s concentration. The monthly variation showed a cyclical trend, with low values observed from June to November and high values from December to May. In addition, the spatiotemporal distribution of ozone concentration was affected by natural factors and anthropogenic factors. Regarding natural factors, TCO concentration was positively correlated with temperature, wind field, and vegetation coverage, but negatively with precipitation in southwest China. Regarding anthropogenic factors, TCO concentration showed a significant positive correlation with regional GDP, oxides of nitrogen (NOx), and volatile organic compounds (VOCs) in most areas of China. Clustering of backward air trajectories revealed that northwest and southeast airflows led to a higher TCO concentration in northeast China. These further indicate that the variation of TCO concentration was affected by many factors, but temperature, wind field, and the emissions of NOx and VOCs were the key factors.

Green city air measurement and health exercise big data monitoring based on remote sensing images and sensors

The current technological solution that can carry out wide coverage, low cost, long-term observation and collection of large-scale regional information is satellite remote sensing technology, which can help people improve the level of development in many fields. Nowadays, people are facing a serious environmental problem in the process of social development: air pollution. It is very important to study the principle of its production. In the past, ground monitoring can usually provide a long time sequence and high-precision pollutant concentration. Many meteorological monitoring stations are sparsely distributed and cannot effectively monitor and analyze the spatial distribution of atmospheric pollutants. This article will the detection of the spatial distribution of the smaller pollutants and their concentration changes are the main targets of information collection, and the method used is an inversion algorithm based on satellite remote sensing technology. Through the use of satellite technical characteristics to observe and analyze the atmosphere and analyze its correlation with the smaller pollutant parameters in the air, use the AOT retrieval algorithm and the AOT retrieval method with NDVI low-resolution processing to collect satellites The obtained data was processed and analyzed, and two AOT inversion models were successfully obtained. • Long-term observation and collection of large-scale regional information by using satellite remote sensing technology. • Nowadays, people are facing a serious environmental problem. • Detection of the spatial distribution of the smaller pollutants. • Use the AOT retrieval algorithm and the AOT retrieval method with NDVI low-resolution processing.

Aircraft-based observation of gaseous pollutants in the lower troposphere over the Beijing-Tianjin-Hebei region

To investigate the spatial and vertical distribution of atmospheric pollutants (SO2, NOx, CO and O3), aircraft-based measurements (model: Yun-12, 12 flights, 27 h total flight time) were conducted from near the surface up to 2400 m over the Beijing-Tianjin-Hebei (BTH) region between June 17th and July 22nd 2016. The results showed that high concentrations of primary gaseous pollutants (SO2, NOx, CO) were generally present in Beijing, Tianjin, Langfang and Tangshan areas, while high values of O3 frequently appeared in areas far from the city. The flights at noon and dusk measured higher O3 concentrations at 600 m and lower O3 concentrations at higher altitudes, implying a strong influence by photochemical production. Back trajectory analysis suggested that the high levels of gaseous pollutants, especially at 600 m, were associated with pollution sources transported from the southerly direction during the observation period. The first simultaneous vertical distribution measurements using aircraft and tethered balloon were conducted in Gaocun (a rural site between Beijing and Tianjin) on June 17th. The results indicated that an inversion layer at the top of the planetary boundary layer (PBL) significantly suppressed vertical exchange through the PBL and resulted in a “two-layer” vertical distribution of pollutants above and below the PBL. Additionally, a residual high O3 layer (79.9 ± 2.5 ppb, 500–1000 m) was observed above the PBL, and it contributed to the surface peak O3 level at noon through downward transport along with the opening up of the PBL. These results indicate that coupled effects of horizontal and vertical transport should be investigated in future studies to improve the chemical transport models used to study the vertical distribution and regional transport over the BTH region.

Environmental effect of denitrification of structural glass by coating TiO2

This study aims to reduce the concentration of nitrogen in the indoor and outdoor atmosphere and its harmful compounds. Nitrogen dioxide is a gas emitted mainly by automobiles, trucks, power plants, and some industrial plants, with the highest concentrations of nitrogen dioxide in terms stops the good distribution of atmospheric pollution which led to higher COVID-19 cases in recent trends. By establishing chemical coatings on the building materials will have a significant effect. The exterior modification on the glass is done by mixing silica gel along with titanium dioxide to adsorb the accumulated NO2 present in the buildings. Here, spray coating and dip coating technologies were used to coat the solution on the normal glass. The coating was found to be hydrophobic and showed better performance in the fastness test results. The size of the film is 45 to 55 nm. The percentage of adsorption confined to 20%. The least number of days of the period of replacement was found to be 24 days in this research for the most vulnerable conditions having air pollution levels greater than 500μgm3. Finally, our study proves that establishing coatings can significantly reduce air pollution by reducing the percentage of NO2 by 20% in a particular environment.

Handling Missing Data in Large-Scale MODIS AOD Products Using a Two-Step Model

Aerosol optical depth (AOD) is a key parameter that reflects the characteristics of aerosols, and is of great help in predicting the concentration of pollutants in the atmosphere. At present, remote sensing inversion has become an important method for obtaining the AOD on a large scale. However, AOD data acquired by satellites are often missing, and this has gradually become a popular topic. In recent years, a large number of AOD recovery algorithms have been proposed. Many AOD recovery methods are not application-oriented. These methods focus mainly on to the accuracy of AOD recovery and neglect the AOD recovery ratio. As a result, the AOD recovery accuracy and recovery ratio cannot be balanced. To solve these problems, a two-step model (TWS) that combines multisource AOD data and AOD spatiotemporal relationships is proposed. We used the light gradient boosting (LightGBM) model under the framework of the gradient boosting machine (GBM) to fit the multisource AOD data to fill in the missing AOD between data sources. Spatial interpolation and spatiotemporal interpolation methods are limited by buffer factors. We recovered the missing AOD in a moving window. We used TWS to recover AOD from Terra Satellite’s 2018 AOD product (MOD AOD). The results show that the MOD AOD, after a 3 × 3 moving window TWS recovery, was closely related to the AOD of the Aerosol Robotic Network (AERONET) (R = 0.87, RMSE = 0.23). In addition, the MOD AOD missing rate after a 3 × 3 window TWS recovery was greatly reduced (from 0.88 to 0.1). In addition, the spatial distribution characteristics of the monthly and annual averages of the recovered MOD AOD were consistent with the original MOD AOD. The results show that TWS is reliable. This study provides a new method for the restoration of MOD AOD, and is of great significance for studying the spatial distribution of atmospheric pollutants.

Spatial distribution characteristics of PM2.5 and PM10 in Xi’an City predicted by land use regression models

PM2.5 and PM10 could increase the risk for cardiovascular and respiratory diseases in the general public and severely limit the sustainable development in urban areas. Land use regression models are effective in predicting the spatial distribution of atmospheric pollutants, and have been widely used in many cities in Europe, North America and China. To reveal the spatial distribution characteristics of PM2.5 and PM10 in Xi'an during the heating seasons, the authors established two regression prediction models using PM2.5 and PM10 concentrations from 181 monitoring stations and 87 independent variables. The model results are as follows: for PM2.5, R2 = 0.713 and RMSE = 8.355 μg/m3; for PM10, R2 = 0.681 and RMSE = 14.842 μg/m3. In addition to the traditional independent variables such as area of green space and road length, the models also include the numbers of pollutant discharging enterprises, restaurants, and bus stations. The prediction results reveal the spatial distribution characteristics of PM2.5 and PM10 in the heating seasons of Xi’an. These results also indicate that the spatial distribution of pollutants is closely related to the layout of industrial land and the location of enterprises that generate air pollution emissions. Green space can mitigate pollution, and the contribution of traffic emission is less than that of industrial emission. To our knowledge, this study is the first to apply land use regression models to the Fenwei Plain, a heavily polluted area in China. It provides a scientific foundation for urban planning, land use regulation, air pollution control, and public health policy making. It also establishes a basic model for population exposure assessment, and promotes the sustainability of urban environments.

Application of WRF-Chem to simulate air quality over Northern Vietnam.

The WRF-Chem (Weather Research and Forecasting with Chemistry) model is implemented and validated against ground-based observations for meteorological and atmospheric variables for the first time in Northern Vietnam. The WRF-Chem model was based on HTAPv2 emission inventory with MOZCART chemical-aerosol mechanism to simulate atmospheric variables for winter (January) and summer (July) of 2014. The model satisfactorily reproduces meteorological fields, such as temperature 2m above the ground and relative humidity 2m above the ground at 45 NCHMF meteorological stations in January, but lower agreement was found in those simulations of July. PM10 and PM2.5 concentrations in January showed good temporal and spatial agreements to observations recorded at three CEM air monitoring stations in Phutho, Quangninh, and Hanoi, with correlation coefficients of 0.36 and 0.59. However, WRF-Chem model was underestimated with MFBs from - 27.9 to - 118.7% for PM10 levels and from - 34.2 to - 115.1% for PM2.5 levels. It has difficulty in capturing day-by-day variation of PM10 and PM2.5 concentrations at each station in July, but MFBs were in the range from - 27.1 to - 40.2% which is slightly lower than those in January. It suggested that further improvements of the model and local emission data are needed to reduce uncertainties in modeling the distribution of atmospheric pollutants. Assessment of biomass burning emission on air quality in summer was analyzed to highlight the application aspect of the WRF-Chem model. The study may serve as a reference for future air quality modeling using WRF-Chem in Vietnam.