Invited review articleSource apportionment of airborne particulates through receptor modeling: Indian scenario
Graphical abstract
Introduction
Airborne particulates are distinguished as multi-component mixtures originated from a wide range of sources, subsequently evolved through several microphysical processes like nucleation, coagulation and condensation before ultimately scavenging off either through wet or dry deposition (Kumar et al., 2015). Association of airborne particulates with human health, crop yield, regional circulation systems, climate dynamics and many other sectors of earth's system is well established in numerous scientific literatures (Ramanathan and Feng, 2009). Implications of airborne particulate are typically regional as predominant particulate species have comparably lower residence time in contrast to long-lived greenhouse gases. However, trans-boundary movement of particulates amplifies the quantum of impacts to greater distances (Ramanathan and Feng, 2009, Banerjee et al., 2011a, Kumar et al., 2015). Particulate diversity in Indian subcontinent is extremely diverse and complex which requires methodical understanding in terms of composition, morphology and mixing state, size distribution and chemical evolution. Among others, particulate morphology and chemical heterogeneities principally regulate its optical properties, volatilities, interactions and phase transformations in different ways and therefore, efforts have been made over the years to study atmospheric particulates as a function of size, shape and chemical characteristics. Particulate morphology and chemical characteristics are essentially functions of associated sources and therefore, it is extremely essential to be characterized for proper estimation. Source apportionment of airborne particulates essentially quantifies the contribution of individual sources to particulate loading based on source and receptor characteristics and in certain cases, with nature of pollutants. Such may be accomplished either through analyzing specific tracers in bulk filter analysis or by numerical/statistical analysis of specific parameter with prevailing meteorological variables or by coupling emission inventory information with dispersion models. In that way, three principal SA techniques are (a) chemical transport models based upon pollutant composition driven by meteorological variables (Banerjee et al., 2011a, Belis et al., 2013), (b) receptor-oriented models based on analysis of chemical data acquired at receptor sites (Balachandran et al., 2000, Srivastava et al., 2008), and (c) emission inventories and dispersion models (Laupsa et al., 2009, Banerjee et al., 2011b).
A number of SA studies for different atmospheric pollutants with some degree of certainty are available in India with majority of studies being conducted using receptor models (RMs) based on monitored particulate concentrations and their source profile. Receptor models are broadly classified into microscopic and chemical methods based on the nature of particle characteristics opted for simulation. Microscopic RM analyzes the morphological features of airborne particulate through optical and scanning electron microscopes which are efficient enough to characterize aerosols in mixing states (Pipal et al., 2011). However, applicability of microscopic RM limits in large-scale as it mostly yields qualitative products (Pant and Harrison, 2012) and confines in identifying inorganic compounds (Shi et al., 2008). In contrast, chemical RM utilizes the chemical composition of airborne particles for identification and apportionment of specific sources. The foundation of all receptor based models is mass conservation which may simply be explained by Eq. 1:where, C is the particulate concentration profile in the receptor site, S denotes source contribution which needs to be measured, F is the particulate source profile and e denotes error between the measured and predicted concentrations. However, mass balance equation itself based on certain assumptions is critical for specific RM techniques than for others (Belis et al., 2013). In most of RMs, the system is considered as quasi-stationary representing statistically insignificant variations in source profile with time. Additionally, evolved particulate species are required to be chemically inactive during its aerial transport. For a proper SA, these assumptions are essentially required to be satisfied, except which definite source profiling may not be achieved or RMs may under/overestimate the individual contribution of particular source (Belis et al., 2013). Additionally, the concept of RMs is based on proper identifications and quantification of specific signatory molecules which virtually establish missing links between sources and receptors. Chemical signatures of specific sources are used to be extremely sensitive and as these signatures gradually evolve with time, may undergo chemical phase transformations and eventually be masked, which critically limits its applications as a tracer. Therefore, selection of the specific RMs for SA studies is extremely important as only few RMs can tolerate deviations of pre-identified assumptions (Watson et al., 2008, Belis et al., 2013). These RMs especially consider selective losses of particular tracers caused by phase transformations and ultimately re-introduce it in the analysis as an error-input.
The present submission only synthesizes the results archived in SA research articles and scientific reports published in the Indian context and available in abstract and citation database of peer-reviewed literature. Particulate sources are summarized and quantitatively evaluated to reduce uncertainties in identifying specific airborne particulate sources. A total of 90 research articles originated in a span of 1985–2014 and available in citation database of peer-reviewed literature were scrutinized. Interestingly, SA studies in India initiated way back in 1985, however, researchers were only aspired for particulate SA studies from 2005 onwards which share 80% (72) of the total scientific publications (90) (Fig. 1a). Until 1990s, there were only 9 publications (10% of total) available typically originated using EF (42%) and FA (33%), while only 3 instances were there when advanced RMs like PCA (17%) and CMB (8%) were in use (Fig. 1b). Unavailability of regional source profile may possibly restrict the use of advanced RM. Since 2000, SA of airborne particulate established itself as a principal research domain (90% of publications) to atmospheric scientists possibly due to raising concern of aerosol induced adverse health impacts and more precisely its association with regional climate change. Since 2010–14, a total of 81 publications were found involving SA of particulates involving many advanced RMs likewise EF (34%), FA (3%), PCA (36%), PMF (15%), UNMIX (3%) and CMB (10%). However, in most of the cases SA was only performed for PM10 and SPM and only in few instances, PM2.5 was considered as a particulate metric. For the entire SA study, most preferred particulate metrics were PM10 (41%) followed by PM2.5 (26%) and SPM (22%). The trend is well comparable to that of European SA case studies (Belis et al., 2013) where significant proportions of SA have been carried out for PM10 (56%) followed by PM2.5 (37%) and SPM (1%). For both instances, SA for ultrafine particulates was relatively less (India: 10% and Europe: 6%) signifying specific requirement of regional case studies emphasizing on ultrafine particulates, which are supposed to be predominately anthropogenic and carcinogenic in nature. In India, considerable amount of particulate SA was carried out from 2010 and 5 years of research resulted to staggering 44 publications (49% of total). Fig. 2 indicates the geographical distribution of SA studies that have been conducted in India. It is evident that most of SA studies have been performed in and around Delhi, Mumbai, Chennai and Kolkata with some contributions from Hyderabad, Tirupati, Durg, Kanpur, Agra and Chandigarh.
A comprehensive analysis on airborne particulate loading and its spatial distribution has also been extensively reviewed. Such meta-analysis clearly indicates the presence of substantial particulate loading especially in the context of Indo-Gangetic Plain (IGP) which requires adequate source segregation for effective implementation of control strategies. Emphases were made to isolate individual species that were characteristics of particulate composition of a specific location. Assignment of specific tracers to precise source categories was also evaluated. Conclusively, a comprehensive review has been made for particulate SA studies in the Indian perspective yielding a quantitative estimation of most relevant particulate sources and there temporal variations.
Section snippets
Regional heterogeneity of airborne particulates
Airborne particulates emitted from specific sources composed of unique chemical signature molecules and fractional abundance of these molecules essentially serve as an input for receptor models. Airborne particulates include chemical heterogeneity at spatio-temporal levels and therefore, there characteristics are highly region specific (Banerjee et al., 2011b, Banerjee and Srivastava, 2011c, Kumar et al., 2015). Numerous literatures are available concerning chemical speciation of airborne
Selection of source signature
Source apportionment of airborne particulate essentially requires particulate speciation information which is critically analyzed to identify the presence of certain species which are presumed to have evolved from identified sources, transported through atmospheric turbulence and eventually assessed in the receptor site. During the course of SA, these unique species are essentially considered to be chemically isolated and supposed to carry unique identification marks of the respective sources (
Source apportionment and receptor modeling
Airborne particulate chemistry is typically controlled by its constituent species and regional meteorology. Again particulate species is the function of associated sources. Therefore, assessment and possible quantification of particulate sources help to develop conceptual model of source–receptor association. SA is the technique to identify responsible sources of airborne particulates and their contribution based on particulate speciation information in receptor sites. Based on mass balance
Temporal pattern of particulate source profile in India
For the proceeding section, a review has been conducted on published articles on particulate SA using RMs in Indian scenario to understand temporal variation of particulate sources within different geographical region. The intension was to specifically characterize particulate sources both in terms of natural and anthropogenic and possibly quantify them. Although, we wish to draw a pattern of temporal variation in particulate SA for entire India, however, that did not materialize due to
Conclusions and way forward
The present review initially describes the existing status of airborne particulate in different geographical regions within India. Integration of different field research identifies several regional hotspots where air quality has been extensively modified by the presence of tropospheric aerosols. Subsequent efforts were made to identify specific trends of aerosol variation essentially unique to a geographical region. Due to vast geographical distributions and prevailing meteorological
Acknowledgment
The present submission is mutually supported by University Grants Commission, New Delhi (F. No. 41-1111/2012, SR) and Department of Science and Technology, New Delhi (F. No. SR/FTP/ES-52/2014). The authors duly acknowledge the guidance and cooperation provided by Director, IESD-BHU and Dean, FESD-BHU.
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