Aerosol Optical Density Research Articles

Cardiovascular, respiratory and all-cause (natural) health endpoint estimation using a spatial approach in Malaysia

In 2016, the World Health Organization (WHO) estimated that approximately 4.2 million premature deaths worldwide were attributable to exposure to particulate matter 2.5 μm (PM2.5). This study assessed the environmental burden of disease attributable to PM2.5 at the national level in Malaysia. We estimated the population-weighted exposure level (PWEL) of PM10 concentrations in Malaysia for 2000, 2008, and 2013 using aerosol optical density (AOD) data from publicly available remote sensing satellite data (MODIS Terra). The PWEL was then converted to PM2.5 using Malaysia's WHO ambient air conversion factor. We used AirQ+ 2.0 software to calculate all-cause (natural), ischemic heart disease (IHD), stroke, chronic obstructive pulmonary disease (COPD), lung cancer (LC), and acute lower respiratory infection (ALRI) excess deaths from the National Burden of Disease data for 2000, 2008 and 2013. The average PWELs for annual PM2.5 for 2000, 2008, and 2013 were 22 μg m-3, 18 μg m-3 and 24 μg m-3, respectively. Using the WHO 2005 Air Quality Guideline cut-off point of PM2.5 of 10 μg m-3, the estimated excess deaths for 2000, 2008, and 2013 from all-cause (natural) mortality were between 5893 and 9781 (95 % CI: 3347–12,791), COPD was between 164 and 957 (95 % CI: 95–1411), lung cancer was between 109 and 307 (95 % CI: 63–437), IHD was between 3 and 163 deaths, according to age groups (95 % CI: 2–394) and stroke was between 6 and 155 deaths, according to age groups (95 % CI: 3–261). An increase in estimated health endpoints was associated with increased estimated PWEL PM2.5 for 2013 compared to 2000 and 2008. Adhering the ambient PM2.5 level to the Malaysian Air Quality Standard IT-2 would reduce the national health endpoints mortality.

Air Quality Interpretation of Four Geographically Distinct Hot Spot States of India-An Appraisal Using Aerosol Optical Depth and Particulate Matter

The application of Moderate Resolution Imaging Spectroradiometer-Aerosol Optical Depth (MODIS-AOD) for Air Quality (AQ) assessment has contributed significantly by making use of a spatiotemporal relationship between ground-level particulate matter and aerosol optical density at both city and state levels. Traditional ground-based site-specific particulate matter monitoring method has found a profound gap in their spatial coverage. Such challenging situations prevail over the progressive development of the combined usage of ground monitoring technique along with the MODIS-AOD product (with 10 km spatial resolution). This was achieved and derived by assembling the satellite sensor, Terra as a tool for the regional-based specific studies for monitoring airborne particles. Their analytical linear association was evaluated and explored their feasibility for monitoring either Respirable Suspended organic Matter (RSPM) or AQI in spatiotemporally distinct geographical sites situated in four States of India. Examined the interrelationship between RSPM-AOD against meteorological drivers through Principal Component Analysis (PCA) and Quantitative Risk Assessment (QRA) of the focussed four zones. Elevated Air Pollution was noticed in the urban and industrial cities of Pune, Kochi, and Chennai. They were flanked by various industrial clusters and the substantial personal handling of vehicles. A region-wise RSPM-AOD correlation was recorded for the categorized areas: WS1, WS2, SW, and ES. Each zone was subsequently judged and a noteworthy association was linked between the ground-monitored RSPM data and the retrieved AOD output. This means of records could represent the aerosol component; consequently, infer their sources of origin and in later days could come up with reasonable emission control channels. States of India Maharashtra, Karnataka, Kerala, and Tamil Nadu, are categorized as WS1, WS2, SW, and ES respectively.

A high resolution spatiotemporal fine particulate matter exposure assessment model for the contiguous United States

Currently available nationwide prediction models for fine particulate matter (PM2.5) lack prediction confidence intervals and usually do not describe cross validated model performance at different spatiotemporal resolutions and extents. We used 41 different spatiotemporal predictors, including data on land use, meteorology, aerosol optical density, emissions, wildfires, population, traffic, and spatiotemporal indicators to train a machine learning model to predict daily averages of PM2.5 concentrations at 0.75 sq km resolution across the contiguous United States from 2000 through 2020. We utilized a generalized random forest model that allowed us to generate asymptotically-valid prediction confidence intervals and took advantage of its usefulness as an ensemble learner to quickly and cheaply characterize leave-one-location-out CV model performance for different temporal resolutions and geographic regions. Using a variable importance metric, we selected 8 predictors that were able to accurately predict daily PM2.5, with an overall leave-one-location-out cross validated median absolute error of 1.20 μgm3, an R2 of 0.84, and confidence interval coverage fraction of 95%. When considering aggregated temporal windows, the model achieved leave-one-location-out cross validated median absolute errors of 0.99, 0.76, 0.63, and 0.60 μgm3 for weekly, monthly, annual, and all-time exposure assessments, respectively. We further describe the model's cross validated performance at different geographic regions in the United States, finding that it performs worse in the Western half of the country where there are less monitors. The code and data used to create this model are publicly available and we have developed software packages to be used for exposure assessment. This accurate exposure assessment model will be useful for epidemiologists seeking to study the health effects of PM2.5 across the continental United States, while possibly considering exposure estimation accuracy and uncertainty specific to the the spatiotemporal resolution and extent of their study design and population.

The Arctic Polar Vortex Response to Volcanic Forcing of Different Strengths

AbstractTropical volcanic eruptions injecting sulfur into the stratosphere are assumed to not only scatter radiation and cool Earth's surface but also alter atmospheric circulation and in particular to strengthen the stratospheric polar vortex in boreal winter. The exact impact is difficult to estimate because of the small number of well observed eruptions and the high internal variability of the vortex. We use large (100‐member) ensembles of simulations with an Earth system model for idealized volcanic aerosol distributions resulting from sulfur injections between 2.5 and 20 Tg. We suggest the existence of a threshold somewhere between 2.5 and 5 Tg(S) below which the vortex does not show a detectable response to the injection. This nonlinearity is introduced partly through the infrared aerosol optical density which increases much stronger than linear with increasing particle size occurring for increasing injection amount. Additionally, the dynamical mechanism causing the vortex strengthening seems not to set in for small aerosol loading. Furthermore, we add to the recent discussion concerning a possible downward propagation of the circulation response leading to a winter warming in Northern Eurasia. At latitudes northward of about 50°N, our simulations do show such an average warming pattern that is statistically significant for injections of 10 Tg(S) or more.

Comparative analysis of different vegetation indices with respect to atmospheric particulate pollution using sentinel data

Several remote sensing based indices have been developed for studying vegetation using varied combinations of spectral bands. However, for regions like Gautam Buddha Nagar (GBN) district where the atmospheric condition is highly influenced by particulate matter loading and human-induced pollution, such indices produce faulty results because of the effects of scattering and absorption in the atmosphere. To reduce these impacts on vegetation indices, atmospheric correction becomes essential. The general objective of this study is to evaluate two non-atmospherically corrected vegetation indices viz. Normalized Difference Vegetation Index (NDVI); Soil-Adjusted Vegetation Index (SAVI) and two atmospherically corrected vegetation indices viz. Enhanced Vegetation Index (EVI); Atmospherically Resistant Vegetation Index (ARVI) with particular reference to GBN district which has high atmospheric aerosol presence. The spatio-temporal distribution of Aerosol Optical Density (AOD) and four vegetation indices for three months March (winter), June (summer) and October (post-monsoon) of year 2018 are analysed statistically. The mean AOD in all three seasons was observed to be above 0.05 and near to 1 indicating hazy conditions in the study area. Nine statistical image quality measures were employed such as Peak Signal to Noise Ratio (PSNR), entropy, Root Mean Square Error (RMSE), Relative Average Spectral Error (RASE), Standard Deviation (SD), Correlation Coefficient (CC), ERGAS, Mean Absolute Deviation (MAD) and Mean Absolute Percentage Error (MAPE), respectively to determine the best suitable index to study vegetation in highly polluted areas. The results indicated that the ARVI represents more enhanced vegetation information with respect to quantifying temporal variation of vegetation in all three seasons, especially in areas with high atmospheric particulate pollution.

Predicting Daily Urban Fine Particulate Matter Concentrations Using a Random Forest Model.

The short-term and acute health effects of fine particulate matter less than 2.5 μm (PM2.5) have highlighted the need for exposure assessment models with high spatiotemporal resolution. Here, we utilize satellite, meteorologic, atmospheric, and land-use data to train a random forest model capable of accurately predicting daily PM2.5 concentrations at a resolution of 1 × 1 km throughout an urban area encompassing seven counties. Unlike previous models based on aerosol optical density (AOD), we show that the missingness of AOD is an effective predictor of ground-level PM2.5 and create an ensemble model that explicitly deals with AOD missingness and is capable of predicting with complete spatial and temporal coverage of the study domain. Our model performed well with an overall cross-validated root mean squared error (RMSE) of 2.22 μg/m3 and a cross-validated R2 of 0.91. We illustrate the daily changing spatial patterns of PM2.5 concentrations across our urban study area made possible by our accurate, high-resolution model. The model will facilitate high-resolution assessment of both long-term and acute PM2.5 exposures in order to quantify their associations with related health outcomes.

Relationship between aerosol optical depth and population density in typical area of east China

Relationship between aerosol optical depth and population density in typical area of east China

Statistical corruption in Beijing's air quality data has likely ended in 2012

Abstract This research documents changes in likely misreporting in official air quality data from Beijing for the years 2008–2013. It is shown that, consistent with prior research, the official Chinese data report suspiciously few observations that exceed the politically important Blue Sky Day threshold, a particular air pollution level used to evaluate local officials, and an excess of observations just below that threshold. Similar data, measured by the US Embassy in Beijing, do not show this irregularity. To document likely misreporting, this analysis proposes a new way of comparing air quality data via Benford's Law, a statistical regularity known to fit air pollution data. Using this method to compare the official data to the US Embassy data for the first time, I find that the Chinese data fit Benford's Law poorly until a change in air quality measurements at the end of 2012. From 2013 onwards, the Chinese data fit Benford's Law closely. The US Embassy data, by contrast, exhibit no variation over time in the fit with Benford's Law, implying that the underlying pollution processes remain unchanged. These findings suggest that misreporting of air quality data for Beijing has likely ended in 2012. Additionally, I use aerosol optical density data to show the general applicability of this method of detecting likely misreporting in air pollution data.

Measuring tropospheric vertical distribution and vertical column density of NO2 by multi-axis differential optical absorption spectroscopy

The inversion method of the vertical profile and vertical column density (VCD) of tropospheric NO2 using multi-axis differential optical absorption spectroscopy (MAX-DOAS) is investigated in this paper. An inversion method of two-step procedure is operated. In this method firstly the aerosol vertical profile is retrieved. Then the vertical distribution of trace gases is retrieved based on the corresponding aerosol status. Nonlinear optimal estimation algorithm is extended to acquire NO2 profile to reduce the dependence of the inversion on priori information. It is more advantageous to automatically obtain trace gases profile. At first we investigate how to calculate some parameters (weighting function, the covariance matrices of measurement, and a priori information) of the algorithm and design nonlinear iteration strategy suited to the region where NO2 vertical distribution usually shows rapid variation. Then this inversion algorithm is verified by computer simulation in the cases of box profile and elevated profile of NO2. It is indicated that the distribution of NO2 below 2 km could be well rebuilt and the retrieval accuracy of surface-near NO2 volume mixing ratio is 0.6%. The study of how accurately this algorithm can rebuild the same true profile in three aerosol status of low aerosol, high aerosol and elevated aerosol indicates that similar retrieval results could be acquired. In addition, the effect of wrong aerosol status on the retrieving of NO2 profile and the error sources of this algorithm are analyzed. After that a continuous observation is reported in the city of Hefei. NO2 VCDs derived from MAX-DOAS are compared with those from satellite observations, and the correlation coefficient is 0.85. The surface-near NO2 concentrations measured by MAX-DOAS are compared with those from LP-DOAS, and the correlation coefficient is 0.76. In addition, the simplified MAX-DOAS inversion method of obtaining the trace gas profile usually uses invariable typical aerosol status as input. The comparison with the tropospheric NO2 VCD from simplified method indicates that the using of invariable typical aerosol status would cause large deviation of NO2 VCD, and its maximum relative deviation is about 112%. So exactly acquiring aerosol status, aerosol optical density especially, is necessary to exactly retrieve tropospheric NO2 vertical column density.

The analysis of solar UVB radiation as a function of solar global radiation, ozone layer thickness and aerosol optical density

Incident solar radiation (insolation) is attenuated by two different phenomena, (i) atmospheric scattering by air molecules, water vapor and aerosols, and (ii) atmospheric absorption by ozone, water and carbon dioxide. The degree of terrestrial solar radiation attenuation is a function of its optical path length, i.e., the distance the Sun’s ray traverse through the Earth’s atmosphere prior to being incident on the its surface. The attenuation by atmospheric scattering, irrespective of source, is an inverse function of the wavelength. Absorption of insolation in the atmosphere is due mainly to ozone in the ultraviolet range and water vapor in the infrared range of the solar spectrum. Ozone absorption decreases with increasing wavelength and above 350 nm there is no absorption. Thus, a priori, any changes in either the ozone layer thickness (OLT) and/or aerosol optical density (AOD) will have a greater effect on ultraviolet radiation, in general, and on UVB in particular. An empirical correlation that determines the UVB radiation intensity as a function of solar global radiation, OLT, AOD and optical path length as represented by the air mass is presented and validated by an independent database. In addition, a parameter sensitivity study was performed on the empirical correlation using two different methods. The application of the empirical correlation as a function of hour type (i.e., clear, partially cloudy and cloudy) was also investigated.

Determination of the atmospheric aerosol optical density by multi axis differential optical absorption spectroscopy

In this work, a method to determine atmospheric aerosol optical density from multi axis differential optical absorption spectroscopy (MAX-DOAS) observations was described. It basically utilizes the differential absorption structures of the oxygen collision complex (O4) in the UV and visible wavelength regions to derive information on aerosol optical properties. Based on radiative transfer model with appropriate aerosol single scattering albedo, asymmetry parameter and profile, atmospheric aerosol optical density was retrieved in an iterative process by comparison with measured O4 slant column densities at 360 nm. The retrieved value was verified through comparisons with sun photometer CE318.

Climate forcing by the volcanic eruption of Mount Pinatubo

We determine the volcano climate sensitivity λ and response time τ for the Mount Pinatubo eruption, using observational measurements of the temperature anomalies of the lower troposphere, measurements of the long wave outgoing radiation, and the aerosol optical density. Using standard linear response theory we find λ = 0.15 ± 0.06 K/(W/m2), which implies a negative feedback of −1.4 (+0.7, −1.6). The intrinsic response time is τ = 6.8 ± 1.5 months. Both results are contrary to a paradigm that involves long response times and positive feedback.

Photolysis frequency of O3 to O(1D): Measurements and modeling during the International Photolysis Frequency Measurement and Modeling Intercomparison (IPMMI)

The International Photolysis Frequency Measurement and Modeling Intercomparison (IPMMI) took place at Boulder, Colorado, from 15 to 19 June 1998 and offered the opportunity to test how well experimental techniques and theoretical models can determine the photolysis frequency of O3 → O(1D) in the troposphere. Different techniques measured the downwelling 2π sr component of j(O1D) at the ground and were blindly compared to each other. Moreover, theoretical j(O1D) model results were blindly compared to data measured under clear sky at relatively low aerosol optical density. Six experimental groups operated one chemical actinometer (CA), six spectroradiometers (SR), and four filter radiometers (FR). General good agreement with deviations less than 10% among the radiometers (SR and FR) was found for solar zenith angles (SZA) less than 60°, provided that the instruments used similar absorption cross sections, quantum yields, and temperatures for deriving j(O1D). The deviations were generally larger at high solar zenith angles and reached a factor of 2 in some cases. Two spectroradiometers and one filter radiometer showed excellent agreement with each other and with the chemical actinometer at all solar zenith angles up to at least 80° within typically 5%. These radiometers used recently published O(1D) quantum yield data and explicitly considered the temperature dependence of j(O1D). This good agreement shows that each of the different categories of instruments (CA, SR, and FR) is in principle capable of accurate determinations of j(O1D). A large sensitivity was found to the choice of data for the O(1D) quantum yield. The best agreement between spectroradiometry and chemical actinometry was obtained when recently published quantum yield data were used. The IPMMI study thus supports the quantum yield recommendation by National Aeronautics and Space Administration‐Jet Propulsion Laboratory [Sander et al., 2003] and International Union of Pure and Applied Chemistry (IUPAC) (http://www.iupac-kinetic.ch.cam.ac.uk; data sheet POx2 from 2001). Fifteen models that were operated by 12 model groups participated in the comparison of modeled j(O1D) with measured data. Most models agreed within 15% with the spectroradiometer‐derived j(O1D) values under clear sky at SZA < 75°, provided that they used similar absorption cross sections, quantum yields, and temperatures. While most models simulated the measured actinic flux quite well, significant deviations in j(O1D) were observed in cases when outdated O(1D) quantum yield data or inappropriate temperature data were used.

Vertical and horizontal aerosol spectral extinction at a rural location in southern Italy

The vertical extinction of the aerosol has been measured with a multiwavelength sunphotometer at a rural location in southern Italy. All measurements were performed during a period with relatively stable weather condition, thus it could be expected to have measured always the same air mass at least within each day. The direct solar radiation was recorded at wavelengths between 400 and 1100 nm with a resolution of 0.5 nm. Calibration of the instrument was performed by means of a Langley plot at an elevation of approximately 3000 m. From these measurements, vertical optical depths have been derived for a series of days in June 1993. The spectral extinction coefficient of the atmospheric aerosol at the same location has been measured by means of a telephotometer. The radiance of a target at a distance of 12 km was measured at nine wavelengths in the visible. Thus the extinction coefficient of the aerosol contained within a conical volume of about 450,000 m3 and a length of 12 km has been measured. The daily variation usually followed the same pattern: a decrease in extinction coefficient in the morning and in the early afternoon and an increase toward the evening. This variation correlated well with the change in humidity, so that it can be assumed that the aerosol particles have decreased their size due to evaporation of water in the morning and uptake of water in the evening. The regular daily pattern of the horizontal aerosol extinction coefficient normally was not followed by the vertical aerosol optical density, but on the other hand, changes in vertical extinction have occurred on some days, which had no effect on the horizontal extinction. Vertical extinction measurements were inverted to obtain aerosol size distributions. Inversions were obtained by the Twomey‐Phillips method and they confirm the presence of a hygroscopic aerosol as suggested directly by the variation of the extinction coefficients against the relative humidity. The aerosol undergoes very clear processes of growth which are well correlated with the behavior of the humidity. Overall, the type of aerosol we have measured could be classified as rural aerosol. This kind of aerosol is typical of the boundary layer of clean continental area and is composed prevalently by water‐soluble substances and in minor abundance by dustlike aerosol.

Influence of aerosol optical properties on surface temperatures computed with a radiative-convective model

Calculations on the effects of aerosols (i.e. suspended particles) have been shown to lead to heating or cooling in atmospheric models, depending on the size distribution of the aerosols, the height of the aerosol layer, and nature of the underlying surface. This work reports a study of the influence of different aerosol optical properties on surface temperature. The calculated surface temperatures are shown to be relatively insensitive to the real part of the refractive index and to the aerosol size distribution assumed. The sensitivity to surface albedo is similar for three aerosol types characteristic of marine aerosols, continental aerosols and stratospheric aerosols. For an aerosol composed of limonite or silicate, an increase in the absorptive component of the refractive index n 2 increases the calculated surface temperature for a constant global average airborne aerosol density as shown below. Surface albedo Surface temperature change for 0.1 increase in n 2 0.07 (oceans) 0.4 K 0.60 (snow and ice) 1.0 K It can be seen that the heating is increased 2–3 times as the surface albedo is increased by an order of magnitude. A 0.1 increase in n 2, corresponds very roughly to a factor of two increase in the percentage of solar absorption by an average particle. It would be useful to be able to determine from the results of this study, if global average aerosols heat or cool the atmosphere. Unfortunately our knowledge of the actual global aerosol distribution, optical properties and optical density is inadequate to make this determination.

Preliminary solar spectro-photometric measurements of aerosol optical density at Lagos, Nigeria

Solar spectrophotometric measurements of the aerosol optical density during the dry dusty (Harmattan) season at two carefully selected sites around the Lagos metropolis are presented. At both sites, a probable contribution of the “remnant”, smaller-size, Saharan dust, borne by the North East trades, is indicated in the total aerosol loading of the ambient air. This would tend to increase on days with favourable meteorological conditions such as that dictated by the position of the Inter-Tropical Discontinuity (ITD). The values of the aerosol optical density at industrial and rural sites were very similar. Data for the daytime pattern of the aerosol optical density are also presented.

Influence of aerosol cloud height on the change in the atmospheric radiation balance due to aerosols

A radiative-convective atmospheric model for 35°N latitude in April is used to demonstrate the influence of aerosol cloud height on the change in the atmospheric radiation balance and temperature profile due to aerosols. Three different aerosol optical densities (0.065, 0.325 and 0.650) are considered as well as three mean aerosol cloud heights, corresponding to pressures of 958, 418 and 41.5 mb. In all cases considered, the surface temperature difference due to aerosols ranges between −3 and +0.4°K, with small magnitudes corresponding either to high aerosol clouds or to high surface albedo. The effect of surface albedo ω s is included by considering ω s, values of 0.07, 0.3 and 0.6. Aerosols at all heights produce two opposing effects in the atmosphere: 1. (1) they reduce the magnitude of the total radiative cooling of the atmosphere, resulting in an effective “heating” at the earth's surface, 2. (2) they increase the “reflectivity” of the earth-atmosphere system to solar radiation and thus reduce the amount of solar energy absorbed resulting in an effective “cooling” at the earth's surface. Effect (1) apparently results from a “trapping” of the radiation by the aerosol and the absorption of this radiation by O 3, H 2O and CO 2. A low-lying aerosol with an optical density ten times the present background value, when situated over a surface such as water ( ω s = 0.07) causes a 1.5 per cent decrease in the radiative cooling of the atmosphere relative to the present cooling rate. (The effect due to a low-lying aerosol having the background optical density τ = 0.065 was found to be negligible.) Accompanying the 1.5 per cent “heating” effect was a 3.8 per cent decrease in solar flux absorbed in the earth-atmosphere system. The combined heating and cooling produces a surface temperature difference of −3°K. For aerosols near the surface and over a reflecting surface such as snow ( ω s = 0.6) an aerosol optical density ten times the present background value produces a ~ 0.7 per cent decrease in the present value of the radiative cooling of the atmosphere. Accompanying this “heating” effect is a negligible decrease in the solar radiation flux absorbed in the earth-atmosphere system. The combined effect in this case results in a surface temperature increase of 0.4°K.

Skylight and Aerosol in Thailand During the Dry Winter Season

Solar and skylight measurements were made in southern Thailand from late February to early April of 1969. The aerosol optical density (basis 10) was rather large, ranging from 0.07 to 0.28 at lambda0.5 microm and varied with about lambda(-2) in the range 0.5 < lambda < 1.6 microm. The skylight scattering phase function was relatively flat and showed little spectral dependence. The log aerosol size distribution seems close to r(-4). The origin of the turbid low level air from the South China Sea and Philippine Sea poses the question of the nature of the aerosol.