Seasonal correlation of aerosols with soil moisture, evapotranspiration, and vegetation over Pakistan using remote sensing

Aerosols have a severe impact on the Earth's climate, human health, and ecosystem. To understand the impacts of aerosols on climate, human health, and the ecosystem we must need to understand the variability of aerosols and their optical properties. Therefore, we used Aqua-MODIS retrieved aerosol optical depth (AOD) (550 nm) and Angstrom exponent (AE) (440/870) data to analyze the Spatio-temporal seasonal variability of aerosols and their relationship with different meteorological parameters over Pakistan from 2002 to 2021. High (>0.5) AOD values were observed during the summer season and low (<0.8) in the spring season. AE values were observed to be high (>1) in the northern regions of Pakistan indicating the dominance of fine mode particles during the winter season. Moreover, AOD showed a positive correlation with Relative Humidity (RH), Evapotranspiration, Wind speed (WS), and Temperature. On the other hand, it showed a negative correlation with Soil moisture (SM), Normalized difference vegetation index (NDVI), and precipitation over Pakistan. Therefore, considering the outcomes of this study will help policymakers to understand the spatiotemporal variability of aerosols and their seasonal correlation with different meteorological parameters.

Temporal and Spatial Variations of Satellite-Based Aerosol Optical Depths, Angstrom Exponent, Single Scattering Albedo, and Ultraviolet-Aerosol Index over Five Polluted and Less-Polluted Cities of Northern India: Impact of Urbanization and Climate Change

It is widely acknowledged that factors such as population growth, urbanization's quick speed, economic growth, and industrialization all have a role in the atmosphere's rising aerosol concentration. In the current work, we assessed and discussed the findings of a thorough analysis of the temporal and spatial variations of satellite-based aerosol optical parameters such as Aerosol Optical Depth (AOD), Angstrom Exponent (AE), Single Scattering Albedo (SSA), and Ultraviolet-Aerosol Index (UV-AI), and their concentration have been investigated in this study over five polluted and less-polluted cities of northern India during the last decade 2011–2020. The temporal variation of aerosol optical parameters for AOD ranging from 0.2 to 1.8 with decadal mean 0.86 ± 0.36 for Patna region shows high value with a decadal increasing trend over the study area due to rise in aerosols combustion of fossil fuels, huge vehicles traffic, and biomass over the past ten years. The temporal variation of AE ranging from 0.3 to 1.8 with decadal mean 1.72 ± 0.11 for Agra region shows high value as compared to other study areas, which indicates a comparatively higher level of fine-mode aerosols at Agra. The temporal variation of SSA ranging from 0.8 to 0.9 with decadal mean 0.92 ± 0.02 for SSA shows no discernible decadal pattern at any of the locations. The temporal variation of UV-AI ranging from -1.01 to 2.36 with decadal mean 0.59 ± 0.06 for UV-AI demonstrates a rising tendency, with a noticeable rise in Ludhiana, which suggests relative dominance of absorbing dust aerosols over Ludhiana. Further, to understand the impact of emerging activities, analyses were done in seasonality. For this aerosol climatology was derived for different seasons, i.e., Winter, Pre-Monsoon, Monsoon, and Post-Monsoon. High aerosol was observed in Winter for the study areas Patna, Delhi, and Agra which indicated the particles major dominance of burning aerosol from biomass; and the worst in Monsoon and Post-Monsoon for the Tehri Garhwal and Ludhiana study areas which indicated most of the aerosol concentration is removed by rainfall. After that, we analyzed the correlation among all the parameters to better understand the temporal and spatial distribution characteristics of aerosols over the selected region. The value of r for AOD (550 nm) for regions 2 and 1(0.80) shows a strong positive correlation and moderately positive for the regions 3 and 1 (0.64), mostly as a result of mineral dust carried from arid western regions. The value of r for AE (412/470 nm) for region 3 and (0.40) shows a moderately positive correlation, which is the resultant of the dominance of fine-mode aerosol and negative for the regions 5 and 1 (− 0.06). The value of r for SSA (500 nm) for regions 2 and 1 (0.63) shows a moderately positive correlation, which explains the rise in big aerosol particles, which scatters sun energy more efficiently, and the value of r for UV-AI for regions 1 and 2 shows a strong positive correlation (0.77) and moderately positive for the regions 3 and 1 (0.46) which indicates the absorbing aerosols present over the study region.

Ambient concentrations and dosimetry of inhaled size-segregated particulate matter during periods of low urban mobility in Bragança, Portugal

The restrictive measures in place during the COVID-19 pandemic provided a timely scenario to investigate the effects of human activities on air quality, and the extent to which mobility reduction strategies can impact atmospheric pollutant levels. Real-time concentrations of PM₁, PM_2.5 and PM₁₀ were measured using a mobile platform in a small city of Portugal, during morning and afternoon rush hours, in two distinct phases of the pandemic: emergency phase (cold period, lockdown) and calamity phase (warm period, less restricted). The Multiple-Path Particle Dosimetry Model (MPPD) was used to calculate the PM deposition for adults. Large spatio-temporal variabilities and pronounced changes in mean PM concentrations were observed, with lower concentrations in the calamity phase: PM₁ = 2.33 ± 1.61 μg m^-3; PM_2.5 = 5.15 ± 2.77 μg m^-3; PM₁₀ = 23.30 ± 21.53 μg m^-3 than in the emergency phase: PM₁ = 16.85 ± 31.80 μg m^-3; PM_2.5 = 30.92 ± 31.93 μg m^-3; PM₁₀ = 111.27 ± 104.53 μg m^-3. These changes are explained by a combination of meteorological factors and local emissions, mainly residential firewood burning. Regarding regional deposition, PM₁ was the main contributor to deposition in the tracheobronchial (5%) and pulmonary (12%) regions, and PM₁₀ in the head region (92%). In general, total deposition doses were higher for males than for females. This work quantitatively demonstrated that even with a 38% reduction in urban mobility during the lockdown, the use of firewood for residential heating is the main contributor to the high concentrations of PM and the respective inhaled dose.

High Spatiotemporal Resolution PM2.5 Concentration Estimation with Machine Learning Algorithm: A Case Study for Wildfire in California

As an aggregate of suspended particulate matter in the air, atmospheric aerosols can affect the regional climate. With the help of satellite remote sensing technology to retrieve AOD (aerosol optical depth) on a global or regional scale, accurate estimation of PM2.5 concentration has become an important task to quantify the spatiotemporal distribution of AOD and PM2.5. However, due to the limitations of satellite platforms, sensors, and inversion algorithms, the spatiotemporal resolution of current major AOD products is still relatively low. Meanwhile, for the impact of cloud, the AOD products often have a serious data gap problem, which also objectively limits the spatiotemporal coverage of predicted PM2.5 concentration. Therefore, how to effectively improve the spatiotemporal resolution and coverage of PM2.5 concentration under the requisite accuracy is still a grand challenge. In this study, the fused high spatial-temporal resolution AOD data in our previous study were used to estimate the ground PM2.5 concentration through machine learning algorithms, the deep belief network (DBN). The PM2.5 data had spatiotemporal autocorrelation in geostatistics and followed the Gaussian kernel distribution. Hence, the autocorrelation model modified by Gaussian kernel function integrated with DBN algorithm, named Geoi-DBN, was used to estimate PM2.5 concentration. The cross-validation results showed that the Geoi-DBN (R2 = 0.86, RMSE = 6.84 µg m−3) performed better than the original DBN (R2 = 0.67, RMSE = 10.46 µg m−3). The final high quality PM2.5 concentration data can be applied for urban air quality monitoring and related PM2.5 exposure risk assessment such as wildfire.

Aerosol Loading and Radiation Budget Perturbations in Densely Populated and Highly Polluted Indo-Gangetic Plain by COVID-19: Influences on Cloud Properties and Air Temperature

Aerosols emitted in densely populated and industrialized Indo-Gangetic Plain, one of the most polluted regions in the world, modulate regional climate, monsoon, and Himalayan glacier retreat. Thus, this region is important for understanding aerosol perturbations and their resulting impacts on atmospheric changes during COVID-19 lockdown period, a natural experimental condition created by the pandemic. By analyzing 5 years (2016-2020) data of aerosols and performing a radiative transfer calculation, we found that columnar and near-surface aerosol loadings decreased, leading to reductions in radiative cooling at the surface and top of the atmosphere and atmospheric warming during lockdown period. Further, satellite data analyses showed increases in cloud optical thickness and cloud-particle effective radius and decrease in lower tropospheric air temperature during lockdown period. These results indicate critical influences of COVID-19 lockdown on regional climate and water cycle over Indo-Gangetic Plain, emphasizing need for further studies from modeling perspectives.

Climatological trends in satellite-derived aerosol optical depth over North India and its relationship with crop residue burning: Rural-urban contrast

Columnar Aerosol Optical Depths (AOD) over an urban area (Chandigarh) and a rural area (Khera, Fatehgarh Sahib district) situated in the Indo-Gangetic Plains (IGP) of India were analysed to study their temporal heterogeneity in terms of interannual, seasonal and monthly variations. Over the last few decades, IGP has become one of the global hotspots of air pollution due to the increased anthropogenic activities such as traffic, industries, agricultural waste burning etc. Level-2 AODs (550 nm) were retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors onboard NASA's Terra and Aqua satellites, for a period of 14 years (2005-2018). The climatological mean Terra-MODIS (Aqua-MODIS) AOD over the urban location was ~0.497 ± 0.238 (0.474 ± 0.228), whereas over the rural location it was 0.542 ± 0.269 (0.534 ± 0.282). Linear trend analysis estimated an increase in annual mean Terra-MODIS (Aqua-MODIS) AOD at a rate of ~0.009 (0.013) per year over the urban site; whereas over the rural location the rate of increase was ~0.003 (0.004) per year. Results show that the observed increase is ~1.49% (2.41%) of climatological mean AOD over the urban location for Terra-MODIS (Aqua-MODIS), whereas, over the rural location, it was ~0.50% (0.67%). Using the HYSPLIT trajectory model, it was concluded that, during post-monsoon, the observed high AODs can be related to massive crop residue burning in the IGP region. These AOD trends can also be used to track the regional anthropogenic air-pollution changes. An empirical relation between AOD and PM₁₀ was established, which can be used to estimate PM₁₀ over the urban and rural areas of IGP (using MODIS AODs), complementing the sparse ground-based monitoring. Further, satellite-based air pollution data can be used for baseline assessment and understanding the impact of control policies such as National Clean Air Programme and to support formulate evidence-based pollution control strategies.

Evaluation of spatial and temporal heterogeneity of black carbon aerosol mass concentration over India using three year measurements from IMD BC observation network

Extensive measurements of equivalent black carbon (EBC) aerosol mass concentration at fifteen stations of India Meteorological Department (IMD) BC observation network during the period 2016-2018 are used to study the spatial and temporal heterogeneity over India. The sampling sites represent different geographical region of India. Spatial distribution shows higher values of EBC over stations of north India and IGP. Highest annual mean EBC mass concentration during study period was reported at two mega cities New Delhi (13,575 ± 8401 ng/m³) followed by Kolkata (12,082 ± 6850 ng/m³) whereas lowest mean concentration was at Ranichauri (1737 ± 884 ng/m³) followed by Bhuj (2021 ± 1471 ng/m³). Stations located in coastal region of south India reported low concentration of EBC. In order to find out the quantitative contribution of biomass burning (EBC_BB) and fossil fuel (EBC_FF) in total mass concentration of EBC, source apportionment study has been carried out using Aethalometer model. The EBC_FF is the dominant contributor to EBC mass concentration at all the sites in every season, while the highest seasonal biomass burning mass contribution (37%) was observed in the winter at a background site Ranichauri. Maximum concentration of EBC_BB was observed at Srinagar (2671 ng/m³) where as EBC_FF was maximum in Delhi (11,074 ng/m³). Seasonal and diurnal variation studies have also been carried out for all the stations. The EBC mass concentrations exhibited strong seasonality, with the highest values occurring in postmonsoon/winter and the lowest in monsoon season. The higher EBC concentration in postmonsoon/winter seasons was attributed to the increased use of fuel in seasonal emission sources, domestic heating and stagnant meteorological conditions, whereas the low levels in monsoon season were related to the precipitation scavenging. Maximum concentration of EBC (22,409 ± 10,510 ng/m³) was observed in winter season over Kolkata. Our study finds high spatial heterogeneity in EBC concentrations across the study area.

Impact of aerosols on reservoir inflow: A case study for Big Creek Hydroelectric System in California

Accurate and reliable reservoir inflow forecast is instrumental to the efficient operation of the hydroelectric power systems. It has been discovered that natural and anthropogenic aerosols have a great influence on meteorological variables such as temperature, snow water equivalent, and precipitation, which in turn impact the reservoir inflow. Therefore, it is imperative for us to quantify the impact of aerosols on reservoir inflow and to incorporate the aerosol models into future reservoir inflow forecasting models. In this paper, a comprehensive framework was developed to quantify the impact of aerosols on reservoir inflow by integrating the Weather Research and Forecasting model with Chemistry (WRF-Chem) and a dynamic regression model. The statistical dynamic regression model produces forecasts for reservoir inflow based on the meteorological output variables from the WRF-Chem model. The case study was performed on the Florence Lake and Lake Thomas Alva Edison of the Big Creek Hydroelectric Project in the San Joaquin Region. The simulation results show that the presence of aerosols results in a significant reduction of annual reservoir inflow by 4-14%. In the summer, aerosols reduce precipitation, snow water equivalent, and snowmelt that leads to a reduction in inflow by 11-26%. In the spring, aerosols increase temperature and snowmelt which leads to an increase in inflow by 0.6-2%. Aerosols significantly reduce the amount of inflow in the summer when the marginal value of water is extremely high and slightly increase the inflow in the spring when the run-off risk is high. In summary, the presence of aerosols is detrimental to the optimal utilization of hydroelectric power systems.

Ambient black carbon, PM2.5 and PM10 at Patna: Influence of anthropogenic emissions and brick kilns

Particulate Matters like Black Carbon, PM_2.5 and PM₁₀ present in the atmosphere not only poses a threat to human health but also contributes to near-term regional and global atmospheric warming. There has been a large concern of this kind of pollutants in Indo-Gangetic Plains (IGP). Hence, an attempt has been made to see the impact in one of the highly developing city of IGP as Patna. This city has been ranked among the top 100 air polluted cities in the world. To establish the role of BC, PM_2.5, and PM₁₀ on local air quality, continuous measurements were conducted at seven locations of Patna from January to December 2015. The seasonal mass concentration of BC were 13.92±3.48μgm^-3 in the winter, 9.65±3.0μgm^-3 in the pre-monsoon, 5.83±1.90μgm^-3 in the monsoon and 7.86±3.66μgm^-3 in the post-monsoon. Similarly, the seasonal concentrations of PM_2.5 (PM₁₀) were 68.86±18.83μgm^-3 (108.13±21.49μgm^-3) in the winter; 64.62±18.76μgm^-3 (93.45±18.42μgm^-3) in the pre-monsoon; 37.83±11.27μgm^-3 (62.82±14.81μgm^-3) in the monsoon and 40.14±16.66μgm^-3 (64.72±22.40μgm^-3) in the post-monsoon. About 76.67% of PM_2.5 and 87.78% of PM₁₀ concentrations were greater than NAAQ Standards in the winter on a daily basis and 46.74% and 36.96% in the pre-monsoon season. The backward trajectory analysis was also carried out through HYSPLIT model which suggests that the additional source of these pollutants during the winter and pre-monsoon season from the northwest and northern region of Patna. The ratios of PM₁₀/PM_2.5 observed at brick kilns cluster monitoring locations during the brick manufacturing period were significantly higher (0.87-4.48μgμgm^-3) than other monitoring sites and increase the level of these pollutants over the city.

Assessment of aerosols optical properties and radiative forcing over an Urban site in North-Western India

The present work is aimed to analyze aerosols optical properties and to estimate aerosol radiative forcing (ARF) from January to December 2013, using sky radiometer data over Rohtak, an urban site in North-Western India. The results reveal strong wavelength dependency of aerosol optical depth (AOD), with high values of AOD at shorter wavelengths and lower values at longer wavelength during the study period. The highest AOD values of 1.07 ± 0.45 at 500 nm were observed during July. A significant decline in Ångström exponent was observed during April-May, which represents the dominance of coarse mode particles due to dust-raising convective activities. Aerosols' size distribution exhibits a bimodal structure with fine mode particles around 0.17 µm and coarse mode particles with a radius around 5.28 µm. Single scattering albedo values were lowest during November-December at all wavelengths, ranging from 0.87 to 0.76, which corresponds to the higher absorption during this period. Aerosols optical properties retrieved during observation period are used as input for SBDART (Santa Barbara DISORT Atmospheric Radiative Transfer) to estimate the direct ARF at the surface, in the atmosphere and at the top of the atmosphere (TOA). The ARF at the TOA, surface and in the atmosphere are found to be in the range of -4.98 to -19.35 W m^-2, -8.01 to -57.66 W m^-2 and +3.02 to +41.64 W m^-2, respectively. The averaged forcing for the whole period of observations at the TOA is -11.26 W m^-2, while at the surface it is -38.64 W m^-2, leading to atmospheric forcing of 27.38 W m^-2. The highest (1.168 K day^-1) values of heating rate was estimated during November, whereas the lowest value (0.084 K day^-1) was estimated for the February.

The effect of aerosol optical depth on rainfall with reference to meteorology over metro cities in India

Rainfall is a key link in the global water cycle and a proxy for changing climate; therefore, proper assessment of the urban environment's impact on rainfall will be increasingly important in ongoing climate diagnostics and prediction. Aerosol optical depth (AOD) measurements on the monsoon seasons of the years 2008 to 2010 were made over four metro regional hotspots in India. The highest average of AOD was in the months of June and July for the four cities during 3 years and lowest was in September. Comparing the four regions, Kolkata was in the peak of aerosol contamination and Chennai was in least. Pearson correlation was made between AOD with climatic parameters. Some changes in the parameters were found during drought year. Temperature, cloud parameters, and humidity play an important role for the drought conditions. The role of aerosols, meteorological parameters, and their impacts towards the precipitation during the monsoon was studied.

Variability in radiative properties of major aerosol types: a year-long study over Delhi--an urban station in Indo-Gangetic Basin

Aerosol measurements over an urban site at Delhi in the western Ganga basin, northern India, were carried out during 2009 using a ground-based automatic sun/sky radiometer to identify their different types and to understand their possible radiative implications. Differentiation of aerosol types over the station was made using the appropriate thresholds for size-distribution of aerosols (i.e. fine-mode fraction, FMF at 500 nm) and radiation absorptivity (i.e. single scattering albedo, SSA at 440 nm). Four different aerosol types were identified, viz., polluted dust (PD), polluted continent (PC), mostly black carbon (MBC) and mostly organic carbon (MOC), which contributed ~48%, 32%, 11% and 9%, respectively to the total aerosols. Interestingly, the optical properties for these aerosol types differed considerably, which were further used, for the first time, to quantify their radiative implications over this station. The highest atmospheric forcing was observed for PC aerosol type (about +40 W m(-2), along with the corresponding atmospheric heating rate of 1.10 K day(-1)); whereas the lowest was for MBC aerosol type (about +25 W m(-2), along with the corresponding atmospheric heating rate of 0.69 K day(-1)).

Radiative effects of aerosols over Indo-Gangetic plain: environmental (urban vs. rural) and seasonal variations

Aerosol radiative effects over two environmentally distinct locations, Kanpur (urban site) and Gandhi College (rural location) in the Indo-Gangetic plain (IGP), a regional aerosol hot spot, utilizing the measured optical and physical characteristics of aerosols, an aerosol optical properties model and a radiative transfer model, are examined. Shortwave aerosol radiative forcing (ARF) at the top of the atmosphere (TOA) is < -12 W m( - 2) over Kanpur and Gandhi College. ARF at the surface is ≥ -30 W m( - 2). Atmospheric warming is maximum during premonsoon (>30 W m( - 2)). Shortwave atmospheric heating due to aerosols is >0.4 K/day over IGP and peaks during premonsoon at >0.6 K/day due to lower single scattering albedo (SSA) and higher surface albedo. TOA forcing is always less negative over Kanpur when compared to Gandhi College due to lower surface albedo except in postmonsoon owing to higher SSA. This happens as TOA forcing depends on SSA and surface albedo in addition to aerosol optical depth. The magnitude of longwave forcing and atmospheric cooling in an absolute sense is significantly small and contributes only about 20% or less to the net (shortwave + longwave) forcing. Aerosol radiative effects over these two locations, despite differences in aerosol characteristics, are similar, thus confirming that aerosols and their radiative influence get transported due to circulation. ARF over Kanpur and Gandhi College is an order of magnitude higher when compared to greenhouse gas forcing. A large reduction in surface reaching solar irradiance accompanied by large atmospheric warming can have implications on precipitation and hydrological cycle, and these aerosol radiative effects should be included while performing regional-scale aerosol climate assessments.