Zhang Y.J.,Nanjing University of Information Science and Technology |
Zhang Y.J.,Jiangsu Environmental Monitoring Center |
Tang L.L.,Nanjing University of Information Science and Technology |
Tang L.L.,Jiangsu Environmental Monitoring Center |
And 9 more authors.
Atmospheric Chemistry and Physics | Year: 2015
Atmospheric submicron particulate matter (PM1) is one of the most significant pollution components in China. Despite its current popularity in the studies of aerosol chemistry, the characteristics, sources and evolution of atmospheric PM1 species are still poorly understood in China, particularly for the two harvest seasons, namely, the summer wheat harvest and autumn rice harvest. An Aerodyne Aerosol Chemical Speciation Monitor (ACSM) was deployed for online monitoring of PM1 components during summer and autumn harvest seasons in urban Nanjing, in the Yangtze River delta (YRD) region of China. PM1 components were shown to be dominated by organic aerosol (OA, 39 and 41%) and nitrate (23 and 20%) during the harvest seasons (the summer and autumn harvest). Positive matrix factorization (PMF) analysis of the ACSM OA mass spectra resolved four OA factors: hydrocarbon-like mixed with cooking-related OA (HOA + COA), fresh biomass-burning OA (BBOA), oxidized biomass-burning-influenced OA (OOA-BB), and highly oxidized OA (OOA); in particular the oxidized BBOA contributes ~80% of the total BBOA loadings. Both fresh and oxidized BBOA exhibited apparent diurnal cycles with peak concentration at night, when the high ambient relative humidity and low temperature facilitated the partitioning of semi-volatile organic species into the particle phase. The fresh BBOA concentrations for the harvests are estimated as BBOA Combining double low line 15.1 × (m/z 60-0.26% × OA), where m/z (mass-to-charge ratio) 60 is a marker for levoglucosan-like species. The (BBOA + OOA-BB)/ΔCO, (ΔCO is the CO minus background CO), decreases as a function of f44 (fraction of m/z 44 in OA signal), which might indicate that BBOA was oxidized to less volatile OOA, e.g., more aged and low volatility OOA (LV-OOA) during the aging process. Analysis of air mass back trajectories indicates that the high BB pollutant concentrations are linked to the air masses from the western (summer harvest) and southern (autumn harvest) areas. © Author(s) 2015. Source
Dimri A.P.,Jawaharlal Nehru University |
Dash S.K.,Center for Atmospheric Science
Climatic Change | Year: 2012
Northern Indian rivers are primarily fed by wintertime (December, January, February-DJF) precipitation, in the form of snow-yielded by eastward moving synoptic weather systems called Western Disturbances (WDs), over the western Himalayas (WH). This accumulated snow melts during ablation period. In the context of today's warming atmosphere, it is imperative to study the changes in the temperature and precipitation patterns over the WH to assess the impact of global warming on climatic conditions of the region. Keeping that in mind, observational analysis of temperature and precipitation fields is planned. In the present study various climatic indices are analyzed based on wintertime (DJF) data of 30 years (1975-2006) obtained from the Snow and Avalanche Study Establishment (SASE), India. Results indicate enhancement in the surface air temperature across the WH. Percent number of warm (cold) days have increased (decreased) during 1975-2006 over the WH. Further analysis of precipitation reveals slightly decreasing but inconsistent trends. © 2011 Springer Science+Business Media B.V. Source
Hodnebrog o.,University of Oslo |
Hodnebrog o.,CICERO Center for International Climate and Environmental Research |
Berntsen T.K.,University of Oslo |
Dessens O.,Center for Atmospheric Science |
And 16 more authors.
Atmospheric Chemistry and Physics | Year: 2012
The future impact of traffic emissions on atmospheric ozone and OH has been investigated separately for the three sectors AIRcraft, maritime SHIPping and ROAD traffic. To reduce uncertainties we present results from an ensemble of six different atmospheric chemistry models, each simulating the atmospheric chemical composition in a possible high emission scenario (A1B), and with emissions from each transport sector reduced by 5% to estimate sensitivities. Our results are compared with optimistic future emission scenarios (B1 and B1 ACARE), presented in a companion paper, and with the recent past (year 2000). Present-day activity indicates that anthropogenic emissions so far evolve closer to A1B than the B1 scenario.
As a response to expected changes in emissions, AIR and SHIP will have increased impacts on atmospheric O3 and OH in the future while the impact of ROAD traffic will decrease substantially as a result of technological improvements. In 2050, maximum aircraft-induced O3 occurs near 80 N in the UTLS region and could reach 9 ppbv in the zonal mean during summer. Emissions from ship traffic have their largest O3 impact in the maritime boundary layer with a maximum of 6 ppbv over the North Atlantic Ocean during summer in 2050. The O3 impact of road traffic emissions in the lower troposphere peaks at 3 ppbv over the Arabian Peninsula, much lower than the impact in 2000.
Radiative forcing (RF) calculations show that the net effect of AIR, SHIP and ROAD combined will change from a marginal cooling of-0.44 ± 13 mW m-2 in 2000 to a relatively strong cooling of-32 ± 9.3 (B1) or-32 ± 18 mW m-2 (A1B) in 2050, when taking into account RF due to changes in O3, CH4 and CH4-induced O3. This is caused both by the enhanced negative net RF from SHIP, which will change from-19 ± 5.3 mW m-2 in 2000 to-31 ± 4.8 (B1) or-40 ± 9 mW m-2 (A1B) in 2050, and from reduced O3 warming from ROAD, which is likely to turn from a positive net RF of 12 ± 8.5 mW m-2 in 2000 to a slightly negative net RF of-3.1 ± 2.2 (B1) or-3.1 ± 3.4 (A1B) mW m-2 in the middle of this century. The negative net RF from ROAD is temporary and induced by the strong decline in ROAD emissions prior to 2050, which only affects the methane cooling term due to the longer lifetime of CH4 compared to O3. The O3 RF from AIR in 2050 is strongly dependent on scenario and ranges from 19 ± 6.8 (B1 ACARE) to 61 ± 14 mW m-2 (A1B). There is also a considerable span in the net RF from AIR in 2050, ranging from-0.54 ± 4.6 (B1 ACARE) to 12 ± 11 (A1B) mW m-2 compared to 6.6 ± 2.2 mW m-2 in 2000. © 2012 Author(s). Source
Mohan M.,Center for Atmospheric Science |
Gurjar B.R.,Indian Institute of Technology Roorkee
International Journal of Environment and Waste Management | Year: 2010
This paper deals with the modification of a validated and operational heavy gas dispersion model, namely IIT Heavy Gas (IITHG) model-1, to propose a quantitative risk assessment tool named as IITD-QRA model. IITHG model-1 is modified based on the incorporation of appropriate probit equation and other necessary parameters (e.g., equipment failure rates, weather frequency, average population density etc.) to study the sensitivity analysis of various probit relationships in QRA. The large variation in risk estimates from different probits emphasises the need for cautious interpretation of risk estimates and well tested dose response curves based on experiments. © 2010 Inderscience Enterprises Ltd. ©2010 Inderscience Enterprises Ltd. Source
Myhre G.,CICERO Center for International Climate and Environmental Research |
Myhre G.,University of Oslo |
Shine K.P.,University of Reading |
Radel G.,University of Reading |
And 17 more authors.
Atmospheric Environment | Year: 2011
The year 2000 radiative forcing (RF) due to changes in O3 and CH4 (and the CH4-induced stratospheric water vapour) as a result of emissions of short-lived gases (oxides of nitrogen (NOx), carbon monoxide and non-methane hydrocarbons) from three transport sectors (ROAD, maritime SHIPping and AIRcraft) are calculated using results from five global atmospheric chemistry models. Using results from these models plus other published data, we quantify the uncertainties. The RF due to short-term O3 changes (i.e. as an immediate response to the emissions without allowing for the long-term CH4 changes) is positive and highest for ROAD transport (31 mW m-2) compared to SHIP (24 mW m-2) and AIR (17 mW m-2) sectors in four of the models. All five models calculate negative RF from the CH4 perturbations, with a larger impact from the SHIP sector than for ROAD and AIR. The net RF of O3 and CH4 combined (i.e. including the impact of CH4 on ozone and stratospheric water vapour) is positive for ROAD (+16(±13) (one standard deviation) mW m-2) and AIR (+6(±5) mW m-2) traffic sectors and is negative for SHIP (-18(±10) mW m-2) sector in all five models. Global Warming Potentials (GWP) and Global Temperature change Potentials (GTP) are presented for AIR NOx emissions; there is a wide spread in the results from the 5 chemistry models, and it is shown that differences in the methane response relative to the O3 response drive much of the spread. © 2010 Elsevier Ltd. Source