Air pollution and wintertime fog over South Asia is a major concern due to its significant implications for air quality, visibility and health. Using a regional climate model coupled with chemistry, we assess the contribution of the hygroscopic growth of aerosols (ambient–dry) to the total aerosol optical depth and demonstrate that the increased surface cooling due to the hygroscopic effects of aerosols further increases the humidity in the boundary layer and thus enhances the confinement of pollutants through aerosol–boundary layer interactions. This positive feedback mechanism plays an important role in the prevalence of wintertime fog and poor air quality conditions over South Asia, where water vapour contributes more than half of the aerosol optical depth. The aerosol–boundary layer interactions lead to moistening of the boundary layer and drying of the free troposphere, which amplifies the long-term trend in relative humidity over the Indo-Gangetic Plain during winter. Hence, the aerosol–water vapour interaction plays a decisive role in the formation and maintenance of the wintertime fog conditions over South Asia, which needs to be considered for planning mitigation strategies.
South Asia experiences severe air pollution events during the
winter season. Widespread haze and fog over the northern parts of the Indian
subcontinent, especially the Indo-Gangetic Plain (IGP), are associated with
anthropogenic activities and are noticeable even from space during the
winter season (Ali
et al., 2019; Gautam and Singh, 2018; Ghude et al., 2017). Poor air quality
and visibility persisting throughout the winter period has been a major
concern for more than 900 million people living in the IGP (Gautam
and Singh, 2018; Gurjar et al., 2008; Lelieveld et al., 2015). Indeed,
various studies have shown that the winter concentrations of fine particles
(PM
The sources of primary emission of anthropogenic aerosols include
residential, transport, industrial and agricultural sectors (Kumar et al.,
2015b). The extensive burning of stubble in agricultural fields has been
reported to be a major contributor to the formation of haze at the beginning
of winter. Mineral-dust transport from west Asia and the Thar Desert also
causes the deterioration of air quality over the region. In addition to the emission
sources, low temperatures, a shallow boundary layer and low-wind-speed
conditions hinder the vertical and horizontal mixing (ventilation) of
aerosols, which favours the accumulation of pollutants within the boundary
layer (Bharali
et al., 2019; Nair et al., 2007). Even though the aerosol loading within the
boundary layer is very high over the IGP, measurements on board aircraft show
relatively clean free-troposphere conditions. The vertical extent of this
high aerosol loading is thus limited and mostly confined to the first 2 km
near the surface with an exponential decrease above the boundary layer (Babu et al., 2016). Mass concentrations of
fine particles (size
In contrast to the numerous studies on the effects of aerosols on the Indian summer monsoon rainfall characteristics (e.g. see references in Li et al., 2016), the impact of high wintertime aerosol loadings on regional haze and fog conditions has been little explored, although some studies have focused on the implications of regional emission sources for air quality or aerosol loading over the region. For example, Nair et al. (2007) showed that the aerosol variability over the IGP has strong relations with the boundary layer variability, whereas Bharali et al. (2019) reported that the aerosol forcing strongly influences the boundary layer evolution, thus strengthening the accumulation of pollutants near the surface. Hence, boundary layer variability affects the aerosol loading and the aerosol forcing influences the evolution of the boundary layer as reported by several studies over polluted urban centres (Bharali et al., 2019; Ding et al., 2016; Huang et al., 2014; Li et al., 2017; Tie et al., 2017). Similarly, several observational studies have investigated the correlation between meteorological parameters, especially temperature and humidity, with aerosol loadings (Kumar et al., 2015a). However, these observational studies have inherent difficulties in separating the aerosol forcing on meteorological conditions from the effects of meteorology on the aerosol loading. Generally, low temperatures and high humidity are observed over the IGP during winter, when the climate over the region is influenced by the western disturbances originating from the Mediterranean and bringing cold moist air over the aerosol-laden IGP. In addition, irrigation, water bodies (rivers and lakes) and farming activities enhance evapotranspiration and relative humidity in the lower troposphere which, together with high aerosol loadings, lead to extensive and frequent fog events over the region (Gautam et al., 2007; Ghude et al., 2017; Goswami and Sarkar, 2015; Syed et al., 2012).
The effect of aerosols on regional climates depends on the aerosol–radiation
interactions, which are influenced by the water affinity of particles and
the ambient relative humidity. The optical properties of aerosol
(AOD, scattering and extinction coefficient) are enhanced by more than 2
times at conditions of higher relative humidity (
Based on these considerations, in this study, we use a regional climate model (RegCM4; Giorgi et al., 2012) coupled to air chemistry and aerosol models to assess the contribution of the aerosol hygroscopic growth to the total aerosol optical depth over the IGP. Since the total radiative impacts of aerosols on surface temperature, cloud properties and precipitation through various forcing pathways are more comprehensively explored by several studies (e.g. Li et al., 2016), we focus only on the effects of the increase in AOD due to relative humidity. Further, we quantify the effects and feedbacks of the aerosol hygroscopic growth on the regional meteorology, visibility and low-air-quality conditions over the region. The model configuration and experimental details are given in the next section.
For our study, we use the regional climate model version 4 (RegCM4) coupled with an atmospheric chemistry and aerosol module. RegCM4 is a limited-area model with a hydrostatic dynamical core and sigma-pressure vertical coordinates (Giorgi et al., 2012). The Coordinated Regional Downscaling Experiment (CORDEX) South Asia domain is used in this study (Fig. 1) with 50 km horizontal grid spacing, 18 vertical levels and a model top at 50 hPa (Giorgi et al., 2012; Nair et al., 2012; Usha et al., 2020). The meteorological initial and lateral boundary conditions for our simulations are provided by the ERA-Interim reanalysis (Dee et al., 2011) for the three winter seasons (December to February) from November 2014 to March 2017, where the first month of simulation (November) of each year is discarded from the analysis as model spin-up. Optimum-interpolation weekly sea surface temperature data from the National Oceanic and Atmospheric Administration (NOAA) are used as lower boundary conditions over the ocean. The parameterization schemes used in the simulations are (1) for boundary layer, the University of Washington (UW) planetary boundary layer scheme; (2) for convection over land and ocean, the Tiedtke scheme; (3) for radiative transfer, the Community Climate Model (CCM3) scheme; (4) for cloud microphysics, a subgrid explicit moisture scheme; and (5) for land surface, the Biosphere–Atmosphere Transfer Scheme. More details on the model configurations and physics have already been discussed in earlier papers (Ajay et al., 2019; Giorgi et al., 2012; Usha et al., 2020). Note that in the validation and analysis of the model output we always consider the average over the three winter seasons unless otherwise specified.
Study domain centred over South Asia. Colour map shows the topography (km), and circles indicate the near-surface mass loading (
RegCM4 has an online chemistry module, which is extensively used for
understanding aerosol–climate interactions (Nair
et al., 2012; Shalaby et al., 2012; Solmon et al., 2015). The aerosol and
trace gas emission fluxes are adopted from the IIASA dataset, and chemical
boundary conditions are from the global model MOZART (Model for Ozone and
Related chemical Tracers). Gas-phase chemistry is based on the CBMZ
(Carbon-Bond Mechanism version Z) scheme and ISORROPIA II is used for
inorganic aerosols (Shalaby et al., 2012).
The aerosol scheme includes sulfate, nitrate, ammonia, sea salt (two size
bins), mineral dust (four size bins), black carbon (hydrophilic and
hydrophobic) and organic carbon (hydrophilic and hydrophobic). The sources,
sinks, atmospheric processes and transport of the aerosol species are
detailed in Solmon
et al. (2006) and Zakey et al. (2008). The mass
concentration of each aerosol species is converted into optical properties
using a mass extinction cross section, which depends on the ambient relative
humidity and species-specific hygroscopic-growth functions (Solmon et
al., 2006). We use the growth function described by Kiehl et al. (2000) for
sulfate, nitrate and ammonia aerosols, in which the growth function
increases exponentially with humidity. For example, at 80 % relative
humidity, the particle mass extinction cross section increases by a factor
of 3 compared to its dry value. The model emits carbonaceous aerosols as
hydrophobic, and the optical properties of these carbonaceous aerosols are
invariant with relative humidity. These particles change from hydrophobic
to hydrophilic due to ageing at a fixed timescale of 1.15 d
(
RegCM4 has been widely used to investigate aerosol–hydroclimate interactions
and the impacts of various forcings on monsoon characteristics (e.g. Solmon
et al., 2015, and Usha et al., 2020). The model can be run with and
without radiative feedbacks of aerosols. In the former case, aerosols affect
the radiation balance and change the surface temperature and meteorology
through direct and indirect pathways. In the latter, the aerosol radiative
forcing is calculated but it does not have effects on the meteorology,
surface temperature and atmospheric thermodynamics. In the present study,
model simulations with (ambient) and without (dry) hygroscopic growth of
aerosols are named as experiments 1 and 2, respectively. Experimental details
are summarized in Table 1. In the case of the dry-aerosol simulations, we
forced the aerosol hygroscopic-growth functions to be equal to 1 in the
model code. The model runs without meteorological feedbacks (Exp1 and Exp2)
are considered control runs for the ambient- and dry-aerosol cases. Since the
effect of aerosol–radiation interactions on land and meteorological
parameters are switched off (no meteorological feedback), the difference
between these two experiments provides the contribution of hygroscopic
growth to the aerosol properties (
The change in AOD solely due to the meteorological feedback of the total aerosol system
(dry
Experimental details.
Several earlier studies have used RegCM4 to simulate the meteorology of South
Asia (Ajay
et al., 2019; Giorgi et al., 2012; Nair et al., 2012; Usha et al., 2020). In
general, the model captures the basic features of seasonal precipitation
(monsoon), though it is sensitive to the convection schemes used and the
extent of the ocean–atmosphere coupling (Ajay
et al., 2019; Di Sante et al., 2019). Studies on the validation of chemical
constituents simulated by the model are rather limited over South Asia (Nair
et al., 2012; Solmon et al., 2015; Usha et al., 2020). A qualitative
inter-comparison of the chemical composition of aerosols simulated by RegCM4
with in situ measurements at distinct locations over the Indian region is
shown in Fig. 2. The measurements of columnar aerosol optical depth are
taken from AERONET (Aerosol Robotic Network) radiometer observations at
Jaipur, Kanpur, Gandhi College and Delhi. The black carbon measurements were
carried out using Aethalometers installed under the ARFI (Aerosol Radiative
Forcing over India) project. Since the measurements of aerosol composition
are sparse over the Indian region, we have taken values reported from
earlier studies for the winter season, and therefore the organic-carbon and
sulfate measurements are for different years than those of the model
simulations (Ali
et al., 2019; Aswini et al., 2019; George et al., 2008; Ram et al., 2010,
2012; Rengarajan et al., 2011; Safai et al., 2008; Satsangi et al., 2012).
Despite these shortcomings, compared to earlier studies, the present model
configuration simulates black carbon mass loading and AOD which are closer
to the observed values (Nair et
al., 2012). Though RegCM4 has a simple scheme for organic aerosols, the
organic carbon mass concentration broadly matches the observed seasonal mean
values. In fact, most climate and chemical transport models fail to capture
the high aerosol loading over this region, a problem which has been mostly
attributed to the parameterization of stable boundary layer conditions (Nair et al., 2012), unaccounted for
emissions (e.g. Nair et al., 2012, references therein), and biases in simulating relative humidity and precipitation (Chatani and Sharma,
2018; Feng et al., 2016). In the present study, AOD and the near-surface
mass concentrations of black carbon, organic carbon, sulfate and dust
simulated by the model are in the range of values reported by several
studies over the region. One of the main challenges in simulating the AOD
over the region is the accurate simulation of relative humidity, which
affects hygroscopic growth (Chatani and Sharma,
2018). The mean relative humidity estimated from several reanalysis
datasets and measurements in different locations of the IGP varies from 60 % to 80 % (Chatani
and Sharma, 2018; Gautam et al., 2007; Ghude et al., 2017; Goswami and
Sarkar, 2015). A good agreement between measured and simulated (with aerosol
feedback) relative humidity over the IGP (Fig. 2e) is important for the
estimation of aerosol optical properties from simulated speciated aerosol
mass concentrations. The RegCM4-simulated relative humidity values are
approximately 10 % higher than the measured RH, with a mean absolute error of 6.6 % and root mean square error (RMSE) of 7.3 %. During winter,
aerosols are confined within the boundary layer, and changes in the boundary
layer height play a major role in the dilution (ventilation) of aerosols
over the IGP (Bharali
et al., 2019; Nair et al., 2012). Shallow and stable boundary layers
prevail during the simulated winter seasons. A comparison with IGRA
(Integrated Global Radiosonde Archive) radiosonde data indicates that the UW
scheme is able to simulate the boundary layer height over the region
reasonably well (Fig. 2f) with a mean absolute error of 200 m (26 % of
mean boundary layer height) and RMSE of 240 m. Further intercomparison of
modelled and measured PM
Validation of RegCM4-simulated (Exp3) aerosol parameters (
The particulate mass loadings (PM
Wintertime AOD measured using AERONET radiometers and simulated with RegCM4 for ambient and dry humidity conditions with meteorological feedback at
Our study shows that the large day-to-day and spatial variability in AOD over the IGP is mostly contributed by relative humidity (Fig. 3), with lower contributions from changes in source characteristics and synoptic-scale circulation. The simulated AOD at ambient relative humidity matches well with the measured AOD (mean absolute error of 0.12 and RMSE of 0.15), whereas the dry AOD is significantly lower and less variable in time. The standard deviation of measured and simulated AOD at ambient humidity conditions is nearly half of the mean AODs (coefficient of variation of 50 %; Fig. 3), whereas, for dry aerosols, the standard deviation of the AOD is low (0.05 to 0.1), with a coefficient of variance ranging between 20 % and 30 %. All the meteorological conditions, associated processes (winds, chemistry, deposition and transport) and anthropogenic emissions remained the same for dry and ambient AOD simulations, except the hygroscopic growth of AOD with relative humidity for the ambient AOD. Compared to the dry AOD, the ambient AOD shows large variability associated with the variability in humidity. The AOD due to dry aerosols has 10 % to 15 % less variability compared to that of the total AOD.
The AOD due to hygroscopic growth (
In general, the mean AOD over the IGP stations (Kanpur and Gandhi College)
is
Change in
The effects of the increase in AOD solely due to the hygroscopic growth of
particles (
The mean vertical profiles of change in temperature and relative humidity
over the IGP due to total aerosol and hygroscopic effects are shown in
Fig. 6. Significant cooling and associated moistening are noticeable in
the boundary layer followed by a weak drying in the lower free troposphere
(1 to 3 km) and a negligible influence above (
Aerosol-induced surface cooling and weak entrainment of dry air mass from the
free troposphere lead to an increase in relative and specific humidity at
the surface (Fig. 5a). Based on extensive measurements of aerosol and
humidity profiles, Feng et al. (2016) reported up to 30 % underestimation of relative humidity within the
boundary layer and 20 % overestimation in the free troposphere by the
WRF-Chem model over a north Indian station (Nainital) during the winter
season. They cited this dry bias in boundary layer humidity as one of
the major reasons for the underestimation of AOD by climate models over the
region. Most reanalysis datasets (National Centers for Environmental Prediction – NCEP – and European Centre for Medium-Range Weather Forecasts – ECMWF) have a negative bias
(underestimate) in simulating relative humidity over this region, especially
during winter (Chatani
and Sharma, 2018; Feng et al., 2016), which significantly affects the
simulation of aerosol optical depth, aerosol radiative forcing and fog
prediction. The present study shows that the negative bias (underestimation)
of relative humidity could be reduced, especially at high relative
humidities (RH
We analysed reanalysis data and in situ observations for the long-term trend in wintertime relative humidity within the boundary layer and free troposphere over the IGP during the last 4 decades (Fig. 7). In contrast to the global scenario, relative humidity increased over the Indian region at the rate of 1 % per decade, together with a concurrent increase in aerosol loadings (Babu et al., 2013) and the number of foggy days (Ghude et al., 2017; Syed et al., 2012). Based on the above discussions (Fig. 6), it can be argued that the aerosol forcing contributes significantly to the observed increasing trend in wintertime moistening of the boundary layer and enhanced occurrence of fog events over the IGP. The aerosol radiative forcing increases the stability of the atmosphere and decreases the transport of moisture from the boundary layer to the free troposphere, which favours the drying trend in the lower free troposphere shown in Fig. 7b. Earlier studies have also attributed the humidification of the boundary layer and drying of the free troposphere during winter to the aerosol forcing (Li et al., 2017; Tie et al., 2017). Our analysis shows that aerosol feedback processes significantly increase the near-surface relative humidity due to weak turbulent diffusivity in the stratified boundary layer (Bharali et al., 2019; Li et al., 2017). The increase in relative humidity, when surface temperature decreases, is due to the increase in water vapour content in the atmosphere as seen in the specific humidity trend reported by Mukhopadhyay et al. (2017). In contrast to the negative trend in relative humidity in the lower free troposphere during winter (Fig. 7b), Mukhopadhyay et al. (2017) show a positive trend for annual mean humidity, which is largely dominated by the positive trend during summer. Global analyses have shown that most continental regions exhibit a long-term warming trend and decrease in relative humidity (Dai, 2006), which has strong implications for the land–ocean warming contrast (Hodnebrog et al., 2019). The long-term trend in the moistening of the boundary layer and drying of the free troposphere over the Indian region during winter is further amplified by the aerosol radiative forcing, primarily through the hygroscopic growth. However, the masking effects of surface warming by aerosols and the contribution of aerosols to the increasing trend in humidity are yet to be quantified.
Vertical profiles of change in relative humidity and temperature due to the total aerosol effect (Ambient
A regional mean AOD increase of
Frequency of occurrence of
The frequency of occurrence of AOD and PM
In fact, generally calm winds (
As shown in Fig. 10, there also exists an enhancement in near-surface
aerosol mass loading (carbonaceous, inorganics and PM
Change in near-surface mass loading (
Spatial variation in mean visibility over the Indian region for ambient feedback simulation. The percentage variation in visibility changes due to hygroscopic growth with respect to visibility due to dry aerosols is given as line contours.
As discussed above, the AOD increase via hygroscopic growth of aerosols
under high-relative-humidity conditions further decreases the incoming solar
radiation at the surface, which results in enhanced surface cooling
(compared to dry aerosols) and a decrease in the exchanges between the
boundary layer and free troposphere. Aerosol–radiation interactions lead to
a significant increase in cloud cover over the IGP region (2 % to 8 %),
which is further increased by the hygroscopic effect of aerosols. The
increase in cloud cover leads to more sulfate formation and thus again
influence the radiative balance. Hence, the hygroscopic effects of aerosols
significantly strengthen the observed aerosol–boundary layer interactions
over the region (Bharali et al.,
2019). Recent studies have shown that the high aerosol concentrations at the
surface over urban centres are strongly related to positive-feedback
processes associated with the boundary layer and water vapour (Ding
et al., 2016; Huang et al., 2014; Li et al., 2017; Tie et al., 2017). The
surface solar dimming and atmospheric warming due to black carbon in the
upper boundary layer decrease the height of the mixed layer (increasing
stratification) and increase the accumulation of aerosols within the
boundary layer (Bharali
et al., 2019; Ding et al., 2016; Nair et al., 2007). The aerosol-induced
increase in relative humidity (1 %–10 %) over most land regions (Fig. 5),
especially the central IGP, further increases the AOD. Tie et al. (2017) have reported that a
decrease in the dispersion of water vapour leads to a self-amplifying
feedback mechanism through which an increase in relative humidity further
increases the AOD due to hygroscopic growth (
In this work, the regional climate model RegCM4 interactively coupled with
atmospheric chemistry and aerosols is used to investigate the contribution
of the hygroscopic growth of aerosols to the total aerosol optical depth and
its meteorological feedback over the Indian subcontinent. Our analysis
shows that the aerosol hygroscopic growth can contribute up to 40 % of the
total AOD and that feedback processes significantly increase near-surface
relative humidity and decrease lower-free-troposphere humidity. This might
strengthen the long-term trend in boundary layer moistening and free
tropospheric drying over the IGP during winter. We also show that the
inclusion of the meteorological feedback due to the hygroscopic growth of
aerosols (
Our study also highlights the need to increase understanding of aerosol–climate–air quality interactions over the India subcontinent through (i) the inclusion of hygroscopic growth and related feedbacks in climate–chemistry models; (ii) direct measurements of hygroscopic-growth functions of aerosols, which are rather limited over the region (Mandariya et al., 2020); and (iii) measurements and model descriptions of the effect of ageing and mixing state on the water affinity of hydrophobic aerosols. Some model limitations specific to this study are worth noting here. The RegCM4 has a simple organic aerosol module and a single growth function for the hundreds of organic species present in the atmosphere which are characterized by a wide range of affinity towards water vapour. The model does not include the effects of organic aerosols on the water affinity of inorganic aerosols, and in addition the effect of aerosols on cloud characteristics (indirect aerosol effect) is not included. All these aspects of model development are underway in the next version of the RegCM4 modelling system.
Notwithstanding these limitations, our study clearly shows that understanding the interactions of natural factors (moisture fluxes and relative humidity) with anthropogenic aerosols (organic and inorganic) is essential for predicting fog and haze events over the IGP and devising appropriate pollution mitigation strategies. In this regard, the aerosol–water vapour interaction is a unique example of the amplification of anthropogenic forcing (aerosols) by natural agents (water vapour) leading to significant changes in regional climate and air quality. To date, low-air-quality and low-visibility events over the IGP have been considered essentially a problem of emission sources and transport of particles; however, our study highlights the important, and in fact sometimes dominant, contributions of atmospheric water vapour to these events and thus the need to consider this natural factor in air quality assessments and related policymaking.
Data are available upon request from the contact author, Vijayakumar S. Nair (vijayakumarsnair@gmail.com).
The supplement related to this article is available online at:
VSN conceived the research theme. VSN and FG wrote the manuscript. UKH supported the data analysis.
The authors declare that they have no conflict of interest.
The work has been carried out under the Simons Associate Programme of the International Centre for Theoretical Physics (ICTP), Trieste, Italy. Vijayakumar Sivadasan Nair acknowledges the support received from the Aerosol Radiative Forcing over India (ARFI) project of the Indian Space Research Organisation. The authors acknowledge the Central Pollution Control Board (CPCB) for the air quality data.
This research has been supported by the Simons Associate Programme of the International Centre for Theoretical Physics (ICTP), Trieste, Italy.
This paper was edited by Armin Sorooshian and reviewed by two anonymous referees.