Atmospheric Haze Research Articles

Trend analysis and forecast of PM2.5 in Fuzhou, China using the ARIMA model

Atmospheric haze from particulate matter has become a major health concern in many large and medium-sized cities of China. Fine airborne particles, PM2.5, are a major component of haze, and the reasons for their fluctuating concentrations need to be better understood to improve air quality. While much of the air quality data from the China National Environmental Monitoring Centre (CNEMC) has already been analyzed for larger Chinese cities such as Beijing and Shanghai, the data from Fuzhou is the topic of this study. Time series data of pollutant concentrations and meteorological parameters were accessed for Fuzhou from August 2014 to July 2016, covering two cold periods (November through February) and two warm periods (May through July). PM2.5 concentrations were compared with those of other pollutants and with meteorological parameters, and the AutoRegressive Integrated Moving Average (ARIMA) model was applied to forecast PM2.5 concentrations. The correlation analysis of Spearman’s rho showed that PM2.5 concentrations had significant positive correlations with PM10, SO2 and NO2 concentrations, while they had negative correlations with meteorological parameters. The ARIMA results showed that PM2.5 concentrations experienced seasonal fluctuations over the two years, which were higher in the cold periods and lower in the corresponding warm periods, ranging from 23 to 52 μg/m3 and from 19 to 31 μg/m3, respectively. Average PM2.5 concentrations during these same cold periods and warm periods were 35 μg/m3 over the two cold periods, which was 52% higher than the 23 μg/m3 averaged over the two warm periods. Compared to the two observed years, 2014–15 and 2015–16, the forecast of PM2.5 concentrations for 2016–17, ranging from about 15 to 30 μg/m3, exhibited similar seasonal fluctuations but also reduced in the same period, ranging from 19 to 52 μg/m3. It is speculated that the Fuzhou Government's macro-policy on air quality may be one of the reasons for the decrease in PM2.5 concentration during the cold periods. Possible causes were given for the discrepancies between actual and fit values.

Performance analysis of chaotic FSO communication system under different weather conditions

AbstractFree space optics (FSO) is a competent technology for wireless communication providing solutions to bandwidth, cost, and portability challenges in radio frequency communication. This paper presents a numerical approach for securing information in free space by using chaos produced through semiconductor lasers. Laser rate equations are applied to model chaos generated by semiconductor laser, followed by chaos masking scheme to hide the message signal inside the generated chaos before transmission. As FSO communication link availability and efficiency is a major concern in different atmospheric conditions, therefore fog, rain, and haze conditions are analyzed and compared for FSO communication‐based on Q‐factor and eye diagram patterns. The results are further studied for both FSO communication models, ie, with and without applying chaos masking scheme.

Comparison of air quality at different altitudes from multi-platform measurements in Beijing

Abstract. The features of upper-air visibility at altitudes of 0.1, 0.3, and 0.5 km and the two-dimensional haze characteristics in the northwest of downtown Beijing were studied by using a multi-platform analysis during haze episodes between 17 December 2016 and 6 January 2017. Through the multi-platform data analysis in hourly and daily variation, the upper-air visibility increased along with the decrease of PM2.5 mass concentration. And the upper-air visibility on non-haze days was about 3–5 times higher than that on haze days with the ground-based Raman–Mie lidar data between 13 December 2016 and 11 January 2017. The vertical transport of pollutants can be inferred from the delayed variation of upper-air visibility between high altitude and low altitude. In addition, the two-dimensional haze characteristics could be studied by analyzing the correlation between vertical haze parameters (atmospheric boundary layer, haze thickness, and aerosol optical thickness) and horizontal haze parameter (upper-air visibility). The characteristics of multi-parameters have been analyzed and concluded for different haze levels.

Decadal Changes in Seasonal Variation of Atmospheric Haze over the Eastern United States: Connections with Anthropogenic Emissions and Implications for Aerosol Composition

The current seasonal summer maximum in surface fine particulate matter (PM2.5) over the eastern United States has been well established. We find that this seasonality has historically changed substantially, based on long-term quality assured inverse visibility (1/Vis) data over 1946–1998. The median summer/winter 1/Vis ratio increased from about 0.8 over both the southeastern and northeastern United States in the late 1940s to 1.24 over the southeastern United States and to 1.04 over the northeastern United States in the mid-1970s. This ratio exhibits weaker changes in both regions afterward. The observed PM2.5 seasonality after the year 2000 has similar spatial distribution as that in 1/Vis over the mid-1990s, with systematically higher summer/winter ratios which rapidly weaken after the mid-2000s. From 1956 to 1975, stronger increases in 1/Vis occurred in summer than in winter in both regions, associated with increases in sulfur dioxide emissions and reductions in anthropogenic carbonaceous emissions. O...

Basins, fractures and volcanoes: Global cartography and topography of Pluto from New Horizons

The 2015 New Horizons flyby has produced the first high-resolution maps of morphology and topography of Pluto and Charon, the most distant objects so mapped. Global integrated mosaics of Pluto were produced using both LORRI framing camera and MVIC line scan camera data, showing the best resolution data obtained for all areas of the illuminated surface, ∼78% of the body. A unique feature of the Pluto imaging data set is the observation of terrains illuminated only by light scattered from atmospheric haze, allowing us to map terrains in the southern hemisphere that would otherwise have been in darkness. MVIC 4-color data were combined with the panchromatic map to produce full color global maps. Digital elevation models (DEMs) over ∼42% of Pluto were produced using combinations of MVIC hemispheric scans and LORRI mosaics, from which slopes at scales of ∼1 km can be determined. Pluto can be divided into regions each with distinct topographic signatures, corresponding with major physiographic terrain types. Large areas of Pluto are comprised of low-relief moderately cratered plains units. Deeply pitted and glaciated plains east of Sputnik Planitia are elevated ∼0.7 km. The most dominant topographic feature on Pluto is the 1200-by-2000-km wide depression enclosing the bright Sputnik Planitia ice sheet, the surface of which is 2.5-to-3.5 km deep (relative to the rim) and ∼2 km deep relative to the mean radius. The partial ring of steep-sided massifs, several of which are more than 5 km high, along the western margins of Sputnik Planitia produce some of the locally highest and steepest relief on Pluto, with slopes of 40–50°. The second major topographic feature is a complex, eroded, ridge-trough system ∼300–400 km wide and at least 3200 km long extending north-to-south along the 155° meridian. This enormous structure has several kilometers of relief. It may predate the large impact event forming the basin, though some post-Sputnik Planitia deformation is evident. The large depressed, partially walled plain, Hyecho Palus, lies due southwest of Sputnik Planitia. Near the center of Hyecho Palus lie the circular constructional edifices Wright and Piccard Montes. Wright Mons rises 4.5 km above these plains, with a central depression ∼4.5 km deep, whereas Piccard Mons, best observed in haze-light, rises ∼5.5 km above the plains but has a bowl-shaped central depression ∼5.5 km below the plains for a total relief of up to 11 km, the greatest observed on Pluto. Both of these features are interpreted as constructional (volcanic?) in nature. Additional prominent topographic features include a 2–3 km high and ∼600 km wide dome centered on the illuminated IAU pole and the amoeboidal plateaus of “bladed” terrains in the equatorial region, which rise 2–5 km above local terrains and are the highest standing geologic units on the encounter hemisphere. The mean elevations in the integrated DEM for the two radio occultation areas are consistent with the 5–6 km difference in elevation as determined independently by the radio experiment, and a limb profile near the egress point confirms the presence of elevated bladed terrains in that area. Local relief of 3–5 km at massifs, troughs and pits supports conclusions that the icy shell of Pluto is relatively rigid. Numerous examples of topographic control of ice or frost deposition occur across Pluto, including the distinct coloration of the polar dome, the elevated terrains of eastern Tombaugh Regio, and along the ridge-trough system, where ridge tops and fossae rims are covered in different ices than at lower elevations. The topographic hypsogram of Pluto's encounter hemisphere is strongly bimodal due to the large Sputnik Planitia depression. Otherwise the topographic signature of Pluto is controlled by deviations from the otherwise dominant low plains, including elevated bladed terrain plateaus and the depressed volcanic province including Wright and Piccard Montes.

Pluto's haze as a surface material

Pluto's atmospheric haze settles out rapidly compared with geological timescales. It needs to be accounted for as a surface material, distinct from Pluto's icy bedrock and from the volatile ices that migrate via sublimation and condensation on seasonal timescales. This paper explores how a steady supply of atmospheric haze might affect three distinct provinces on Pluto. We pose the question of why they each look so different from one another if the same haze material is settling out onto all of them. Cthulhu is a more ancient region with comparatively little present-day geological activity, where the haze appears to simply accumulate over time. Sputnik Planitia is a very active region where glacial convection, as well as sublimation and condensation rapidly refresh the surface, hiding recently deposited haze from view. Lowell Regio is a region of intermediate age featuring very distinct coloration from the rest of Pluto. Using a simple model haze particle as a colorant, we are not able to match the colors in both Lowell Regio and Cthulhu. To account for their distinct colors, we propose that after arrival at Pluto's surface, haze particles may be less inert than might be supposed from the low surface temperatures. They must either interact with local materials and environments to produce distinct products in different regions, or else the supply of haze must be non-uniform in time and/or location, such that different products are delivered to different places.

Evaluation of forest loss in Balikpapan Bay in the end of 2015 based on Sentinel-1A polarimetric analysis

Satellite remote sensing has proved to be efficient for forest change monitoring. In tropical areas, polarimetric satellite images have a great potential given their ability to see through clouds, smoke and atmospheric haze. For Balikpapan Bay (Borneo, Indonesia), Sentinel-1A acquired images every 24 days during 2015 in both vertically co-polarized and cross-polarized modes. Using series of polarimetric radar images taken before and after an observed event (in this case a fire), information about changes in native forest can be delivered. In this work we detect and delineate areas burnt or damaged by catastrophic fires in autumn 2015. This work demonstrates a potential of satellite radar imagery using a relatively simple method for identification of forest changes. The whole processing chain as presented has been prepared for using open-source software (mainly ESA SNAP). Presented results were compared to both global services (GLAD and FIRMS databases) and local observation (UAV image over burnt area at Bugis canal).

Application of Sentinel-1 satellite to identify oil palm plantations in Balikpapan Bay

Satellite remote sensing has proved to be efficient for monitoring of canopy changes. In tropical areas, optical or multispectral satellite images are very often negatively affected by cloud cover, on the other hand satellites with polarimetric radars have a great advantage given their ability to penetrate clouds, smoke and atmospheric haze. Copernicus Sentinel-1 radar constellation offers both vertically co-polarized and cross-polarized imagery in a relatively high revisit time and resolution. This work describes an approach to identify selected palm oil plantations in Balikpapan Bay, East Kalimantan (Borneo). It gives an overview about advantages for monitoring temporal changes in the tropic environment using radar imagery but also constraints due to ambiguity of canopy type identification. The paper shows a brief comparison with application of multispectral Copernicus Sentinel-2 data and points a roadmap towards a practical application of the technologies.

In Vivo Two-Photon Fluorescence Imaging of the Activity of the Inflammatory Biomarker LTA4H in a Mouse Pneumonia Model.

Severe atmospheric haze caused by industrial pollution has severely affected human health and led to the increasing incidence of cardiopulmonary diseases, including pneumonia. Conventional methods for diagnosis of pneumonia are complicated and tedious, and current clinical imaging techniques might cause organ injuries to some extent. Therefore, an accurate, fast, and intact imaging method must be developed to diagnose pneumonia in the early stages. In this study, we propose a new two-photon fluorescence probe, named as ASPC, for detection of the activity of the inflammatory biomarker LTA4H through specific recognition and cleavage of amides containing the unnatural amino acid l-AspBzl. The activity of LTA4H in the lung tissues of mice was rapidly and accurately monitored for the first time and could be an indicator for diagnosis of pneumonia. The severity of pneumonia in mice caused by haze particulate was determined through imaging the activity of LTA4H as biomarker and confirmed using a commercial ELISA kit of interleukin-1β. This work provides a promising method for clinical detection of pneumonia and for screening specific depressors of LTA4H as potential drug candidates.

Evolution of the spatiotemporal pattern of PM2.5 concentrations in China – A case study from the Beijing-Tianjin-Hebei region

Atmospheric haze pollution has become a global concern because of its severe effects on human health and the environment. The Beijing-Tianjin-Hebei urban agglomeration is located in northern China, and its haze is the most serious in China. The high concentration of PM2.5 is the main cause of haze pollution, and thus investigating the temporal and spatial characteristics of PM2.5 is important for understanding the mechanisms underlying PM2.5 pollution and for preventing haze. In this study, the PM2.5 concentration status in 13 cities from the Beijing-Tianjin-Hebei region was statistically analyzed from January 2016 to November 2016, and the spatial variation of PM2.5 was explored via spatial autocorrelation analysis. The research yielded three overall results. (1) The distribution of PM2.5 concentrations in this area varied greatly during the study period. The concentrations increased from late autumn to early winter, and the spatial range expanded from southeast to northwest. In contrast, the PM2.5 concentration decreased rapidly from late winter to early spring, and the spatial range narrowed from northwest to southeast. (2) The spatial dependence degree, by season from high to low, was in the order winter, autumn, spring, summer. Winter (from December to February of the subsequent year) and summer (from June to August) were, respectively, the highest and lowest seasons with regard to the spatial homogeneity of PM2.5 concentrations. (3) The PM2.5 concentration in the Beijing-Tianjin-Hebei region has significant spatial spillovers. Overall, cities far from Bohai Bay, such as Shijiazhuang and Hengshui, demonstrated a high-high concentration of PM2.5 pollution, while coastal cities, such as Chengde and Qinhuangdao, showed a low-low concentration.

Brief review on climate change and tropical peatlands

In 2008, the very extensive tropical peats were estimated to be about 182 million ha spanning South America, Asia and Africa. About 20.3% (36.9 million ha) of this area exist in Asia. Peats are classified based on their degree of decomposition, namely Fibrists, Hemists, Saprists and Folists. This makes them different in characteristics. The activities of microorganisms vary in different types of peat due to, for example, the sapric layer of well humified peat can provide water and food to microorganisms during heat stress. In another scenario, deeper peat is older and typically has lower levels of labile carbon to provide substrate for microbes compared to surface peat. A complete understanding of the microbial communities in different layers of peat is essential as microorganisms play major roles in peat decomposition and are important to ecosystem processes. These peats are a very important global carbon (C) store or reserve and could severely impact climate change if not managed well. Peatlands can store as much as 40 to 90 Gt C. Mis-management of peats could severely impact the environment particularly the emission of carbon into the atmosphere. For instance, clearing of peatlands using fire has been reported to release an estimated 88 t C ha−1 to the atmosphere. There are several factors which influence the environmental consequences of tropical peat especially in relation to climate change. The main influences are: (i) changes in temperature, (ii) changes in precipitation or rainfall, (iii) changes in atmospheric composition, and (iv) fire and haze. This paper is a brief review on these four influences in relation to climate change. It is apparent from the brief review that there is a need for continued short and long-term research to better understand tropical peats and how they affect our climate. This will hopefully provide the basis for predicting better what could happen under various scenarios.

Atmospheric Circulation, Chemistry, and Infrared Spectra of Titan-like Exoplanets around Different Stellar Types

Abstract With the discovery of ever smaller and colder exoplanets, terrestrial worlds with hazy atmospheres must be increasingly considered. Our solar system’s Titan is a prototypical hazy planet, whose atmosphere may be representative of a large number of planets in our Galaxy. As a step toward characterizing such worlds, we present simulations of exoplanets that resemble Titan but orbit three different stellar hosts: G, K, and M dwarf stars. We use general circulation and photochemistry models to explore the circulation and chemistry of these Titan-like planets under varying stellar spectra, in all cases assuming a Titan-like insolation. Due to the strong absorption of visible light by atmospheric haze, the redder radiation accompanying later stellar types produces more isothermal stratospheres, stronger meridional temperature gradients at mbar pressures, and deeper and stronger zonal winds. In all cases, the planets’ atmospheres are strongly superrotating, but meridional circulation cells are weaker aloft under redder starlight. The photochemistry of hydrocarbon and nitrile species varies with stellar spectra, with variations in the FUV/NUV flux ratio playing an important role. Our results tentatively suggest that column haze production rates could be similar under all three hosts, implying that planets around many different stars could have similar characteristics to Titan’s atmosphere. Lastly, we present theoretical emission spectra. Overall, our study indicates that, despite important and subtle differences, the circulation and chemistry of Titan-like exoplanets are relatively insensitive to differences in the host star. These findings may be further probed with future space-based facilities, like WFIRST, LUVOIR, HabEx, and OST.

On the early studies recognizing the role of sulphuric acid in atmospheric haze and new particle formation

Atmospheric aerosols have been a subject to scientific interest at least since the Age of Enlightenment, including theories concerning the origins of atmospheric haze and dust. Early studies associated haze with geological sources – earthquakes and volcanism – which were believed to be related to the chemistry of sulphuric compounds. Thus, sulphuric acid became the strongest candidate to explain atmospheric new particle formation. The idea was carried over when the first quantitative studies of condensation nuclei and atmospheric chemistry took place during the later part of the 19th century. Laboratory and field measurements by von Helmholtz, Aitken, Kiessling, and Barus, among others, a century ago led to the conclusion that widespread new particle formation occurs in the atmosphere and is caused by sulphuric acid together with water and ammonia – a viewpoint, which has been rediscovered and expanded during the past 25 years.

Research on Diesel Engine Energy Saving and Emission Reduction Based on Air System and NOx Virtual Sensor Model

As of the beginning of 2017, the number of motor vehicles in our country exceeded 300 million. Motor vehicle emissions are one of the most important sources of atmospheric haze. Therefore, vehicle emissions and energy consumption have always been important research directions for emission reduction and energy saving. In this paper, IOC (intake oxygen concentration) observer and feedforward controller of EGR and VGT are designed based on diesel engine air model. NOx virtual sensor model is designed to detect NOx emission as the feedback variable of IOC observer, and achieve the purpose of accurately measuring the amount of NOx, controlling the EGR valve and the VGT blade in real time, reducing the NOx emission of various diesel engines, improving the fuel economy of the engine and reducing the source of the haze, and there is an important reality in this research and the later promotion and social significance.

Effect of Atmospheric Haze Based on Multi-source Remote Sensing Data Considering the Size Effect of Landscape Sources and Sinks

Based on a geo-weighted regression model, this study analyzes the relationship between the landscape patterns of sources and sinks in urban areas and atmospheric haze pollution. First, the classification result of the study area is divided into a number of square grids with side lengths of 2-9 km. Heterogeneity indices at different scales are calculated and compared to select an optimal scale for the following analysis. Then, the category level landscape indices, such as PLAND, PD, COHEDION, LPI, and FRAC_MN, are calculated in each grid. The aerosol optical thickness (AOD) of Wuhan is used to represent the degree of atmospheric haze pollution. Furthermore, the mean value of the pixels in each grid is regarded as the value of the grid's center. Next, the landscape sources and sinks of atmospheric haze pollution are selected based on the analysis of the correlation between landscape indices and AOD. To make the following analysis more efficient, the indices selected previously are determined using their correlation coefficients. Finally, the geo-weighted regression analysis model is used to analyze the relationship between the landscape indices of the category level and AOD. In addition, the influences of industrial, commercial, and residential areas on haze pollution are analyzed based on the result of the classification of urban functional areas. The results show that the heterogeneity of the whole landscape is most obvious at a 6 km scale, so 6 km is the optimal scale for the analysis. The landscape sources of atmospheric haze pollution are the buildings, and the landscape sinks are shrubs and woodland. Reducing the proportion of landscape source area and increasing the degree of fragmentation can cut down aerosol optical thickness. Distributing the landscape sources and sinks evenly and interspersedly could effectively reduce aerosol optical thickness, which represents atmospheric haze pollution. For Wuhan City, the main sources of haze pollution are commercial and residential areas in the city center, representing public sources. Since it is not easy to adjust existing facilities and infrastructure, adjusting built-up areas slightly and planning reasonably for those areas that are not yet built up can reduce atmospheric haze pollution.

Haze Removal Based on a Fully Automated and Improved Haze Optimized Transformation for Landsat Imagery over Land

Optical satellite imagery is often contaminated by the persistent presence of clouds and atmospheric haze. Without an effective method for removing this contamination, most optical remote sensing applications are less reliable. In this research, a methodology has been developed to fully automate and improve the Haze Optimized Transformation (HOT)-based haze removal. The method is referred to as AutoHOT and characterized with three notable features: a fully automated HOT process, a novel HOT image post-processing tool and a class-based HOT radiometric adjustment method. The performances of AutoHOT in haze detection and compensation were evaluated through three experiments with one Landsat-5 TM, one Landsat-7 ETM+ and eight Landsat-8 OLI scenes that encompass diverse landscapes and atmospheric haze conditions. The first experiment confirms that AutoHOT is robust and effective for haze detection. The average overall, user’s and producer’s accuracies of AutoHOT in haze detection can reach 96.4%, 97.6% and 97.5%, respectively. The second and third experiments demonstrate that AutoHOT can not only accurately characterize the haze intensities but also improve dehazed results, especially for brighter targets, compared to traditional HOT radiometric adjustment.

GEOSPATIAL ANALYSIS OF ATMOSPHERIC HAZE EFFECT BY SOURCE AND SINK LANDSCAPE

Abstract. Based on geospatial analysis model, this paper analyzes the relationship between the landscape patterns of source and sink in urban areas and atmospheric haze pollution. Firstly, the classification result and aerosol optical thickness (AOD) of Wuhan are divided into a number of square grids with the side length of 6 km, and the category level landscape indices (PLAND, PD, COHESION, LPI, FRAC_MN) and AOD of each grid are calculated. Then the source and sink landscapes of atmospheric haze pollution are selected based on the analysis of the correlation between landscape indices and AOD. Next, to make the following analysis more efficient, the indices selected before should be determined through the correlation coefficient between them. Finally, due to the spatial dependency and spatial heterogeneity of the data used in this paper, spatial autoregressive model and geo-weighted regression model are used to analyze atmospheric haze effect by source and sink landscape from the global and local level. The results show that the source landscape of atmospheric haze pollution is the building, and the sink landscapes are shrub and woodland. PLAND, PD and COHESION are suitable for describing the atmospheric haze effect by source and sink landscape. Comparing these models, the fitting effect of SLM, SEM and GWR is significantly better than that of OLS model. The SLM model is superior to the SEM model in this paper. Although the fitting effect of GWR model is more unsuited than that of SLM, the influence degree of influencing factors on atmospheric haze of different geography can be expressed clearer. Through the analysis results of these models, following conclusions can be summarized: Reducing the proportion of source landscape area and increasing the degree of fragmentation could cut down aerosol optical thickness; And distributing the source and sink landscape evenly and interspersedly could effectively reduce aerosol optical thickness which represents atmospheric haze pollution; For Wuhan City, the method of adjusting the built-up area slightly and planning the non-built-up areas reasonably can be taken to reduce atmospheric haze pollution.

Surface air quality implications of volcanic injection heights

Air quality implications of volcanic eruptions have gained increased attention recently in association with the 2010 Icelandic eruption that resulted in the shut-down of European air space. The emission amount, injection height and prevailing weather conditions determine the extent of the impact through the spatio-temporal distribution of pollutants. It is often argued that in the case of a major eruption in Iceland, like Laki in 1783–1784, that pollutants injected high into the atmosphere lead to substantially increased concentrations of sulfur compounds over continental Europe via long-range transport in the jet stream and eventual large-scale subsidence in a high-pressure system. Using state-of-the-art simulations, we show that the air quality impact of Icelandic volcanoes is highly sensitive to the injection height. In particular, it is the infinitesimal injections into the lower half of the troposphere, rather than the substantial injections into the upper troposphere/lower stratosphere that contribute most to increased pollutant concentrations, resulting in atmospheric haze over mainland Europe/Scandinavia. Besides, the persistent high pressure system over continental Europe/Scandinavia traps the pollutants from dispersing, thereby prolonging the haze.

A GIS Model for PM10 Exposure from Biomass Burning in the North of Thailand

Human exposure to particulate matter with an aerodynamic diameter below 10 μm (PM10) is found to be associated with biomass burning in Thailand. Recent investigations confirm that primary sources of PM10 are natural forest fires and agricultural waste burning. Incidence of atmospheric haze increases significantly during the dry season from January to April. PM10 exposure in eight provinces in Northern Thailand were determined using GIS through spatial interpolation. Daily average ambient PM10 concentrations from 10 monitoring stations were used as the input data for the GIS model. Three interpolation techniques: Inverse Distance Weighted (IDW), Kriging and Spline, were compared. The predicted PM10concentrations were verified with field measurements. GIS-based maps illustrated the variability of PM10 distribution and high-risk locations, which were found to be associated with wind direction and forest fire frequencies. Mae Hong Son, Chiang Rai and Phrae were found to be at highest risk of PM10 exposure during the dry season.

Comparison of Models on Spatial Variation of PM2.5 Concentration:A Case of Beijing-Tianjin-Hebei Region

Due to the rapid urbanization and increasing energy consumption, air pollution, especially some fine particulates like PM2.5 rise in the context of fast urbanization. PM2.5 pollution has been given considerable attention recent years. High PM2.5 concentration is the main reason for the atmospheric haze in Beijing-Tianjin-Hebei region. Air pollution has become the key issue restricting the sustainable development of Beijing-Tianjin-Hebei region and even the whole country. Long-term exposure to PM2.5 is likely to cause adverse effects on human health. The spatial-temporal variation of air pollution can be characterized by the land use regression model. It is significant to have a good knowledge of spatial characteristics of PM2.5 concentration, which could assist air pollution management and the epidemiological research. This manuscript used air quality data of 104 monitoring sites of Beijing-Tianjin-Hebei region from 1st January 2014 to 31st December, 2014, combined with VⅡRS (visible infrared imaging radiometer) AOD(aerosol optical depth), land use, meteorological factors, road network, population, and pollutant sources distribution to establish the land use regression model by least square method and geographically weighted method respectively. The four models established were least square land use regression model with VⅡRS AOD data, geographically weighted land use regression model with VⅡRS AOD data, least square land use regression model without VⅡRS AOD data and geographically weighted land use regression model without VⅡRS AOD data. And the adjusted R2 values for these four models were 82.13%, 84.87%, 80.45% and 81.99%, respectively. Research results demonstrated that the geographically weighted method performed better than the least square method and improved the land use regression model to a certain extent.