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Spatial Heterogeneity in Near Surface Aerosol Characteristics Across the Brahmaputra Valley

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Spatial Heterogeneity in Near Surface Aerosol Characteristics Across the Brahmaputra Valley Spatial heterogeneity in near surface aerosol characteristics across the Brahmaputra valley Binita Pathak1, Arup Borgohain2, Pradip Kumar Bhuyan1,∗, Shyam Sundar Kundu2, S Sudhakar2, Mukunda M Gogoi3 and Toshihiko Takemura4 1Centre for Atmospheric Studies, Dibrugarh University, Dibrugarh 786 004, India. 2North–East Space Application Centre, Umiam, Shillong, Meghalaya 793 103, India. 3Space Physics Laboratory, Vikram Sarabhai Space Centre, Thiruvananthapuram 695 022, India. 4Research Institute for Applied Mechanics, Kyushu University 6-1 Kasuga-koen, Kasuga, Fukuoka 816-8580, Japan. ∗Corresponding author. e-mail: [email protected] In order to examine the spatial variability of the aerosol characteristics across the Brahmaputra valley, a land campaign was conducted during late winter (February 3–March 2) 2011. Measurements of parti- culate matter (PM, PM10,PM2.5) and black carbon (BC) concentrations were made onboard an interior redesigned vehicle. The length of the campaign trail stretched about 700 km, covering the longitude belt of 89.97◦–95.55◦E and latitude belt of 26.1◦–27.6◦N, comprising 13 measurement locations. The valley is divided into three sectors longitudinally: western sector (R1: 89.97◦–91.75◦E), middle sector (R2: 92.5◦– 94.01◦E) and eastern sector (R3: 94.63◦–95.55◦E). Spatial heterogeneity in aerosol distribution has been observed with higher PM10 and PM2.5 concentrations at the western and middle sectors compared to the eastern sector. The locations in the western sector are found to be rich in BC compared to the other two sectors and there is a gradual decrease in BC concentrations from west to east of the Brahmaputra valley. Two hotspots within the western and middle sectors with high PM and BC concentrations have been identified. The associated physico-optical parameters of PM reveal abundance of PM2.5 aerosols along the entire valley. High population density in the western and middle sectors, together with the contribution of remote aerosols, leads to higher anthropogenic aerosols over those regions. Spectral Radiation-Transport Model for Aerosol Species (SPRINTARS) slightly underestimates the measured PM10 and PM2.5 at the eastern sector while the model overestimates the measurements at a number of locations in the western sector. In general, BC is underestimated by the model. The variation of BC within the campaign trail has not been adequately captured by the model leading to higher variance in the western locations as compared to the middle and eastern locations. 1. Introduction in spatio-temporal distribution, properties, and effects of aerosols. The aerosol abundance is high- The discrete nature of aerosol sources (both natu- est near the surface as most of the aerosol sources ral and anthropogenic) and sinks, the variety of (both natural and anthropogenic) are situated associated microphysical processes during their there. Study of their physico-optical and chemi- atmospheric residence time, and large scale synop- cal parameters are essential for a better understan- tic processes in the atmosphere coupled with long- ding of their role in the atmospheric processes. range transportation lead to large heterogeneity For reliable estimates of their impacts through Keywords. PM10;PM2.5;blackcarbon;SPRINTARS;CWT. J. Earth Syst. Sci. 123, No. 4, June 2014, pp. 651–663 c Indian Academy of Sciences 651 652 Binita Pathak et al. regional scale climatological models, extensive India produces favourable conditions for the observational data is necessary. On the other hand, accumulation of both remote and local aerosols the complex physical and chemical properties of establishing a sharp regional gradient. Sitting in aerosols are the major sources of uncertainty in the the foothills of the Great Himalayas, convective assessment of their impact on climate and envi- activities make the atmospheric constituents pile ronment. In order to reduce these uncertainties, up at higher altitudes in this region (Li et al. accurate measurements of physical, optical, and 2005), which further affects both the regional and chemical properties of the aerosols using multi- global climate, primarily the Asian summer mon- platform measurements (such as ground-based soon. Some reports have also shown that Tibetan networks, ship, aircrafts, balloons, and satellites), plateau and south China are affected by pollu- multi-instrumented field experiments together with tants transported from north–east India (Cao et al. numerical modelling are of great importance (e.g., 2010). Despite its geographical positioning and Kaufman et al. 2001). This, in particular, is essen- uniqueness in topography-orography, this region tial in the south Asian region with all its nat- still remains less explored in terms of atmospheric ural diversities, high population density, diverse constituents. Though much attention is given to living habits, and the growing industrialization the Tibetan Plateau and the Himalayas in recent and urbanization (Moorthy et al. 2008). With this years, the north–eastern part of India was not in view, several multi-platform, multi-institutional explored in any of the aforementioned campaigns thematic field campaigns, viz., Indian Ocean except partly by CAIPEEX. Dibrugarh (27.3◦N, Experiment (INDOEX) (Ramanathan et al. 2001), 94.6◦E, 111 m amsl) is the only location across Arabian Sea Monsoon Experiment (ARMEX) the Brahmaputra valley of north–east India, from (Moorthy et al. 2005), Integrated Campaign for where both short and long term measurements of Aerosols, Gases and Radiation Budget (ICARB) aerosol properties have been made and reported (Moorthy et al. 2008), Cloud–Aerosol Interac- in last few years by Gogoi et al.(2009, 2011)and tion and Precipitation Enhancement Experiment Pathak et al.(2010, 2012, 2013). These studies (CAIPEEX), Winter phase of Integrated Cam- have helped in regional characterization of atmo- paign for Aerosols, gases and Radiation Budget spheric aerosols in the Indian subcontinent w.r.t (W-ICARB) (e.g., Moorthy 2010)mostlyoverthe its north–eastern part. It is now recognized that oceans and land campaigns, viz., Land campaign-I the aerosol abundance in the atmospheric col- (LC I) over southern and coastal India (Moorthy umn is high at Dibrugarh in the pre-monsoon sea- et al. 2005), Land campaign-II (LC II) over Indo- son (March–May), followed by winter (December– Gangetic plains, IGP (ARFI Report 2007–08) and February); the lowest being in the post-monsoon over central Indian region (Jayaraman et al. 2006) season (October–November). The maximum abun- have been conducted. Short-term campaigns such dance of aerosols results in the highest seasonal as those mentioned above have the advantage of aerosol radiative forcing and consequent heating measurements over an extended spatial domain of the atmosphere during pre-monsoon season. On within a short time span that brings out the spe- the other hand, aerosols within the PBL max- cial features of subregions within the campaign imize in winter and are minimum in the mon- area, whereas point observations from any loca- soon season, indicating a heterogeneity between tion provide high temporal span. However, the surface and column aerosol loading over this loca- short duration and scattered distribution of sur- tion. A statistically significant decadal increase face point measurements during a campaign pre- (0.0135 year−1) in the column aerosol burden in vent collection of data required to extract robust terms of aerosol optical depth over Dibrugarh spatial patterns. has been reported by Babu et al. (2013). The In the regional characterization of aerosols over individual contributions of the types of aerosols, south Asia, a study from the north–eastern part of viz., continental average, marine continental aver- India assumes significance owing to its geographi- age, urban/industrial and biomass burning, desert cal position, being surrounded by east Asia, south dust, and unidentified or mixed type, were found east Asia, China and the mainland of India. In to vary seasonally with the highest contribu- addition, the characteristic dense vegetation, vast tion of urban/industrial and biomass burning in water bodies, heavy rainfall pattern and the unique the winter (December–February). Recently, Pathak topography with mountains in the north, east, andBhuyan(2013) have reported similar diur- and south and densely populated Indo-Gangetic nal and seasonal behaviour of scattering and plains towards the west (which makes the region absorbing aerosols over Dibrugarh, which indicates prone to heavy external influence) results in a that both types of aerosols originate from the complex aerosol environment. The blocking by same source. These studies have also shown that mountains all around and convergence effects over the aerosols/pollutants originating from different the foothills of the Himalayas over north–east regions of India and west Asia are transported over Spatial heterogeneity of the surface aerosol characteristics across Brahmaputra valley 653 the IGP through the western corridor towards the measurements were taken at 13 selected locations: Brahmaputra valley. Aerosols from the Bay of Ben- Dhubri–DHB (26.1◦N, 89.97◦E), Gossaigao – GSG gal (BoB) also find their way to the Brahmaputra (26.45◦N, 89.95◦E), Bongaigaon – BNG (26.52◦N, basin through this corridor. This is corroborated 90.5◦E),Nalbari – NBL (26.47◦N, 91.43◦E), Guwahati – by satellite images of intrusion of haze over the GHY (26.17◦N, 91.75◦E), Nagaon – NGN (26.22◦N, IGP and BoB to the north–east as seen in figure 1 92.5◦E),Tezpur – TZU (26.7◦N, 92.83◦E), Bokakhat – (courtesy NASA). Therefore, to examine the spa- BKH (26.63◦N, 93.58◦E), Jorhat – JRH (26.73◦N, tial variability of the aerosol characteristics along 94.01◦E), Sivasagar – SVG (26.95◦N, 94.63◦E), the Brahmaputra valley, a land campaign was Dibrugarh – DBR (27.3◦N, 94.6◦E), Tinsukia – conducted by North–Eastern Space Applications TSK (27.5◦N, 95.36◦E) and Doomdooma – DMD Centre (NESAC) in collaboration with Dibrugarh (27.6◦N, 95.55◦E). In figure 2, the yellow square University, from west to east during the period and red triangles indicate the urban and semi- February 3–March 2, 2011.
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