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Author

Saravanan Arunachalam

Other affiliations: Research Triangle Park
Bio: Saravanan Arunachalam is an academic researcher from University of North Carolina at Chapel Hill. The author has contributed to research in topics: Air quality index & CMAQ. The author has an hindex of 21, co-authored 73 publications receiving 1357 citations. Previous affiliations of Saravanan Arunachalam include Research Triangle Park.


Papers
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TL;DR: In this article, the effect of uncertainties in UAM-V input variables (emissions, initial and boundary conditions, meteorological variables, and chemical reactions) on the uncertainties in ozone predictions was investigated.

198 citations

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TL;DR: In this paper, the authors estimate the incremental contribution of commercial aviation emissions during landing and takeoff (LTO) cycles from three U.S. airports to fine particulate matter (PM2.5) levels using the Community Multiscale Air Quality model.

87 citations

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TL;DR: In this article, the authors examined the surface PM2.5 and premature mortality impacts of halving anthropogenic BC emissions globally and individually from eight world regions and three major economic sectors.
Abstract: . As a component of fine particulate matter (PM2.5), black carbon (BC) is associated with premature human mortality. BC also affects climate by absorbing solar radiation and reducing planetary albedo. Several studies have examined the climate impacts of BC emissions, but the associated health impacts have been studied less extensively. Here, we examine the surface PM2.5 and premature mortality impacts of halving anthropogenic BC emissions globally and individually from eight world regions and three major economic sectors. We use a global chemical transport model, MOZART-4, to simulate PM2.5 concentrations and a health impact function to calculate premature cardiopulmonary and lung cancer deaths. We estimate that halving global anthropogenic BC emissions reduces outdoor population-weighted average PM2.5 by 542 ng m−3 (1.8 %) and avoids 157 000 (95 % confidence interval, 120 000–194 000) annual premature deaths globally, with the vast majority occurring within the source region. Most of these avoided deaths can be achieved by halving emissions in East Asia (China; 54 %), followed by South Asia (India; 31 %), however South Asian emissions have 50 % greater mortality impacts per unit BC emitted than East Asian emissions. Globally, halving residential, industrial, and transportation emissions contributes 47 %, 35 %, and 15 % to the avoided deaths from halving all anthropogenic BC emissions. These contributions are 1.2, 1.2, and 0.6 times each sector's portion of global BC emissions, owing to the degree of co-location with population globally. We find that reducing BC emissions increases regional SO4 concentrations by up to 28 % of the magnitude of the regional BC concentration reductions, due to reduced absorption of radiation that drives photochemistry. Impacts of residential BC emissions are likely underestimated since indoor PM2.5 exposure is excluded. We estimate ∼8 times more avoided deaths when BC and organic carbon (OC) emissions are halved together, suggesting that these results greatly underestimate the full air pollution-related mortality benefits of BC mitigation strategies which generally decrease both BC and OC. The choice of concentration-response factor and health effect thresholds affects estimated global avoided deaths by as much as 56 % but does not strongly affect the regional distribution. Confidence in our results would be strengthened by reducing uncertainties in emissions, model parameterization of aerosol processes, grid resolution, and PM2.5 concentration-mortality relationships globally.

85 citations

Journal ArticleDOI
TL;DR: The public health benefits are dominated by the reduction in cruise SO(x) emissions, so a key uncertainty is the atmospheric modeling of vertical transport of pollution from cruise altitudes to the ground, and comparisons of modeled and measured vertical profiles indicate that this uncertainty is low relative to uncertainties regarding the value of statistical life and the toxicity of fine particulate matter.
Abstract: In jurisdictions including the US and the EU ground transportation and marine fuels have recently been required to contain lower concentrations of sulfur, which has resulted in reduced atmospheric SO(x) emissions. In contrast, the maximum sulfur content of aviation fuel has remained unchanged at 3000 ppm (although sulfur levels average 600 ppm in practice). We assess the costs and benefits of a potential ultra-low sulfur (15 ppm) jet fuel standard ("ULSJ"). We estimate that global implementation of ULSJ will cost US$1-4bn per year and prevent 900-4000 air quality-related premature mortalities per year. Radiative forcing associated with reduction in atmospheric sulfate, nitrate, and ammonium loading is estimated at +3.4 mW/m(2) (equivalent to about 1/10th of the warming due to CO(2) emissions from aviation) and ULSJ increases life cycle CO(2) emissions by approximately 2%. The public health benefits are dominated by the reduction in cruise SO(x) emissions, so a key uncertainty is the atmospheric modeling of vertical transport of pollution from cruise altitudes to the ground. Comparisons of modeled and measured vertical profiles of CO, PAN, O(3), and (7)Be indicate that this uncertainty is low relative to uncertainties regarding the value of statistical life and the toxicity of fine particulate matter.

82 citations

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TL;DR: In this paper, a model inter-comparison study to assess the abilities of steady-state Gaussian dispersion models to capture near-road pollutant dispersion has been carried out with four models (AERMOD, run with both the area-source and volume-source options to represent roadways, CALINE, versions 3 and 4, ADMS and RLINE).
Abstract: A model inter-comparison study to assess the abilities of steady-state Gaussian dispersion models to capture near-road pollutant dispersion has been carried out with four models (AERMOD, run with both the area-source and volume-source options to represent roadways, CALINE, versions 3 and 4, ADMS and RLINE). Two field tracer studies are used: the Idaho Falls tracer study and the Caltrans Highway 99 tracer study. Model performance measures are calculated using concentrations (observed and estimated) that are paired in time and space, since many of the health related questions involve outcomes associated with spatially and temporally distributed human activities. All four models showed an ability to estimate the majority of downwind concentrations within a factor of two of the observations. RLINE, AERMOD-V, and ADMS, also have the capability to predict concentrations upwind of the roadway that result from low-speed meandering of the plume. Generally, RLINE, ADMS, and AERMOD (both source types) had overall performance statistics that were broadly similar, while CALINE 3 and 4 both produced a larger degree of scatter in their concentration estimates. The models performed best for near-neutral conditions in both tracer studies, but had mixed results under convective and stable conditions.

80 citations


Cited by
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TL;DR: The literature on atmospheric particulate maffer (PM), or atmospheric aerosol, has increased enormously over the last 2 decades and amounts now to some 1500-2000 papers per year in the refereed literature.
Abstract: The literature on atmospheric particulate maffer (PM), or atmospheric aerosol, has increased enormously over the last 2 decades and amounts now to some 1500—2000 papers per year in the refereed literature. This is in part due to the enormous advances in measurement technologies, which have allowed for an increasingly accurate understanding of the chemical composition and of the physical properties of atmospheric particles and of their processes in the atmosphere. The growing scientific interest in atmospheric aerosol particles is due to their high importance for environmental policy. In fact, particulate maffer constitutes one of the most challenging problems both for air quality and for climate change policies. In this context, this paper reviews the most recent results within the atmospheric aerosol sciences and thepoticy needs, which have driven much ofthe increase in monitoring and mechanistic research over the last 2 decades. The synthesis reveals many new processes and developments in the science underpinning climate—aerosol interactions and effects of PM on human health and the environment. However, while airborne particulate matter is responsible for globally important influences on premature human mortality, we stijl do not know the relative importance of the different chemical components of PM for these effects. Likewise, the magnitude of the overall effects of PM on climate remains highly uncertain. Despite the uncertainty there are many things that could be done to mitigate local and global problems of atmospheric PM. Recent analyses have shown that reducing black carbon (BC) emissions, using known control measures, would reduce global wanning and delay the time when anthropogenic effects on global temperature would exceed 2°C. Likewise, cost-effective control measures on ammonia, an important agricultural precursor gas for secondary inorganic aerosols (SlA), would reduce regional eutrophication and PM concentrations in large areas of Europe, China and the USA. Thus, there is much that could be done to reduce the effects of atmospheric PM on the climate and the health of the environment and the human population. A prioritized list of actions to mitigate the full range of effects ofPM is currently undeliverable due to shortcomings in the knowledge of aerosol science; among the shortcomings, the roles of PM in global climate and the relative roles of different PM precursor sources and their response to climate and land use change over the remaining decades of this century are prominent. In any case, the evidence from this paper strongly advocates for an integrated approach to air quality and climate policies.

648 citations

Journal ArticleDOI
TL;DR: In this article, the authors examined various bias and error metrics and proposed PM model performance goals (the level of accuracy that is considered to be close to the best a model can be expected to achieve) and criteria that vary as a function of concentration and extinction.

626 citations

Journal ArticleDOI
TL;DR: Most North American studies have shown that areas where low-socioeconomic-status communities dwell experience higher concentrations of criteria air pollutants, while European research has been mixed, but research in these parts of the world is limited.
Abstract: The existing reviews and meta-analyses addressing unequal exposure of environmental hazards on certain populations have focused on several environmental pollutants or on the siting of hazardous facilities. This review updates and contributes to the environmental inequality literature by focusing on ambient criteria air pollutants (including NOx), by evaluating studies related to inequality by socioeconomic status (as opposed to race/ethnicity) and by providing a more global perspective. Overall, most North American studies have shown that areas where low-socioeconomic-status (SES) communities dwell experience higher concentrations of criteria air pollutants, while European research has been mixed. Research from Asia, Africa, and other parts of the world has shown a general trend similar to that of North America, but research in these parts of the world is limited.

526 citations

Journal ArticleDOI
TL;DR: In this paper, the authors describe the scientific and structural updates to the latest release of the Community Multiscale Air Quality (CMAQ) modeling system version 4.7 (v4.7) and points the reader to additional resources for further details.
Abstract: . This paper describes the scientific and structural updates to the latest release of the Community Multiscale Air Quality (CMAQ) modeling system version 4.7 (v4.7) and points the reader to additional resources for further details. The model updates were evaluated relative to observations and results from previous model versions in a series of simulations conducted to incrementally assess the effect of each change. The focus of this paper is on five major scientific upgrades: (a) updates to the heterogeneous N2O5 parameterization, (b) improvement in the treatment of secondary organic aerosol (SOA), (c) inclusion of dynamic mass transfer for coarse-mode aerosol, (d) revisions to the cloud model, and (e) new options for the calculation of photolysis rates. Incremental test simulations over the eastern United States during January and August 2006 are evaluated to assess the model response to each scientific improvement, providing explanations of differences in results between v4.7 and previously released CMAQ model versions. Particulate sulfate predictions are improved across all monitoring networks during both seasons due to cloud module updates. Numerous updates to the SOA module improve the simulation of seasonal variability and decrease the bias in organic carbon predictions at urban sites in the winter. Bias in the total mass of fine particulate matter (PM2.5) is dominated by overpredictions of unspeciated PM2.5 (PMother) in the winter and by underpredictions of carbon in the summer. The CMAQv4.7 model results show slightly worse performance for ozone predictions. However, changes to the meteorological inputs are found to have a much greater impact on ozone predictions compared to changes to the CMAQ modules described here. Model updates had little effect on existing biases in wet deposition predictions.

420 citations