Performance evaluation of chemistry transport models over India

Moorthy, K. Krishna; Beegum, S. Naseema; Srivastava, Nishi; Satheesh, S. K.; Chin, Mian; Blond, Nadège; Babu, S. Suresh; Singh, Shiva Kumar

doi:10.1016/j.atmosenv.2013.01.056

Cited by 66 publications

(89 citation statements)

References 72 publications

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“…The simulation with monthly varying emissions compares slightly better with observations compared to the baseline simulation but still underestimates BC (NMBF = −2.29), OC (NMBF = −4.92), and PM 2.5 (NMBF = −1.34), suggesting that seasonality in emissions has little impact on reducing model bias. The low bias in our model, particularly for BC and OC, is consistent with previous modelling studies using bottom-up emission inventories in South Asia (Ganguly et al, 2009;Nair et al, 2012;Moorthy et al, 2013;Pan et al, 2015) and East Asia (Park et al, 2005;Koch et al, 2009;Fu et al, 2012). The contribution of residential emissions is illustrated by the model simulation where these emissions are switched off, with substantially greater underestimation of BC (NMBF = −5.12), OC (NMBF = −11.46), and PM 2.5 (NMBF = −1.60) concentrations (Fig.…”

Section: Model Evaluationsupporting

confidence: 78%

“…The baseline simulation underestimated observed BC, OC, and PM 2.5 concentrations, with the largest underestimation over East Asia and South Asia, consistent with other modelling studies (Fu et al, 2012;Moorthy et al, 2013;Pan et al, 2015). Applying monthly varying emissions (MACCity emission data set), in place of annual mean emissions (ACCMIP emission), has little improvement on overall model bias but does improve the ability of the model to simulate the observed seasonal variability of aerosol.…”

Section: Discussionsupporting

confidence: 67%

“…The baseline simulation generally captures this seasonality relatively well (correlation coefficient between observed and simulated monthly mean concentrations r > 0.5 at most sites), with minimal improvement with monthly varying anthropogenic emissions. This suggests that meteorological conditions such as enhanced wet deposition during the summer monsoon period are the dominant drivers for the observed and simulated seasonal variability, consistent with other modelling studies for the same region (Adhikary et al, 2007;Moorthy et al, 2013). Model simulations where residential emissions have been switched off show that residential combustion contributes about two-thirds of simulated BC and OC at these locations.…”

Section: Model Evaluationsupporting

confidence: 73%

“…Firstly, emission factors for RSF combustion derived from laboratory experiments are often less than those derived under ambient conditions (Roden et al, 2009). Secondly, models typically underestimate observed aerosol absorption optical depth, BC, and OC over regions associated with large RSF emissions such as in South and East Asia (Park et al, 2005;Koch et al, 2009;Ganguly et al, 2009;Menon et al, 2010;Nair et al, 2012;Fu et al, 2012;Moorthy et al, 2013;Bond et al, 2013;Pan et al, 2015). A further complication is that residential emissions, particularly from residential heating, also exhibit seasonal variability (Aunan et al, 2009;Stohl et al, 2013), but this is rarely implemented within global modelling studies.…”

Section: Introductionmentioning

confidence: 99%

“…For sites in South Africa, we used PM 2.5 and BC mass and aerosol number size distribution (Vakkari et al, 2013). For sites in South Asia, we used BC mass from the Integrated Campaign for Aerosols gases and Radiation Budget (ICARB) field campaign at eight locations across the Indian mainland and islands (Moorthy et al, 2013). For South Asian sites, we also used PM 2.5 , EC, and OC mass, aerosol number size distribution from the island of Hanimaadhoo in the Maldives , and EC and OC measurements from Godavari in Nepal (Stone et al, 2010).…”

Section: In Situ Measurementsmentioning

confidence: 99%

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The impact of residential combustion emissions on atmospheric aerosol, human health, and climate

et al. 2016

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Abstract. Combustion of fuels in the residential sector for cooking and heating results in the emission of aerosol and aerosol precursors impacting air quality, human health, and climate. Residential emissions are dominated by the combustion of solid fuels. We use a global aerosol microphysics model to simulate the impact of residential fuel combustion on atmospheric aerosol for the year 2000. The model underestimates black carbon (BC) and organic carbon (OC) mass concentrations observed over Asia, Eastern Europe, and Africa, with better prediction when carbonaceous emissions from the residential sector are doubled. Observed seasonal variability of BC and OC concentrations are better simulated when residential emissions include a seasonal cycle. The largest contributions of residential emissions to annual surface mean particulate matter (PM 2.5 ) concentrations are simulated for East Asia, South Asia, and Eastern Europe. We use a concentration response function to estimate the human health impact due to long-term exposure to ambient PM 2.5 from residential emissions. We estimate global annual excess adult (> 30 years of age) premature mortality (due to both cardiopulmonary disease and lung cancer) to be 308 000 (113 300-497 000, 5th to 95th percentile uncertainty range) for monthly varying residential emissions and 517 000 (192 000-827 000) when residential carbonaceous emissions are doubled. Mortality due to residential emissions is greatest in Asia, with China and India accounting for 50 % of simulated global excess mortality. Using an offline radiative transfer model we estimate that residential emissions exert a global annual mean direct radiative effect between −66 and +21 mW m −2 , with sensitivity to the residential emission flux and the assumed ratio of BC, OC, and SO 2 emissions. Residential emissions exert a global annual mean first aerosol indirect effect of between −52 and −16 mW m −2 , which is sensitive to the assumed size distribution of carbonaceous emissions. Overall, our results demonstrate that reducing residential combustion emissions would have substantial benefits for human health through reductions in ambient PM 2.5 concentrations.

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Section: Model Evaluationsupporting

confidence: 78%

Section: Discussionsupporting

confidence: 67%

Section: Model Evaluationsupporting

confidence: 73%

Section: Introductionmentioning

confidence: 99%

Section: In Situ Measurementsmentioning

confidence: 99%

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The impact of residential combustion emissions on atmospheric aerosol, human health, and climate

et al. 2016

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Trends in aerosol optical depth over Indian region: Potential causes and impact indicators

et al. 2013

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[1] The first regional synthesis of long-term (back to~25 years at some stations) primary data (from direct measurement) on aerosol optical depth from the ARFINET (network of aerosol observatories established under the Aerosol Radiative Forcing over India (ARFI) project of Indian Space Research Organization over Indian subcontinent) have revealed a statistically significant increasing trend with a significant seasonal variability. Examining the current values of turbidity coefficients with those reported~50 years ago reveals the phenomenal nature of the increase in aerosol loading. Seasonally, the rate of increase is consistently high during the dry months (December to March) over the entire region whereas the trends are rather inconsistent and weak during the premonsoon (April to May) and summer monsoon period (June to September). The trends in the spectral variation of aerosol optical depth (AOD) reveal the significance of anthropogenic activities on the increasing trend in AOD. Examining these with climate variables such as seasonal and regional rainfall, it is seen that the dry season depicts a decreasing trend in the total number of rainy days over the Indian region. The insignificant trend in AOD observed over the Indo-Gangetic Plain, a regional hot spot of aerosols, during the premonsoon and summer monsoon season is mainly attributed to the competing effects of dust transport and wet removal of aerosols by the monsoon rain. Contributions of different aerosol chemical species to the total dust, simulated using Goddard Chemistry Aerosol Radiation and Transport model over the ARFINET stations, showed an increasing trend for all the anthropogenic components and a decreasing trend for dust, consistent with the inference deduced from trend in Angstrom exponent.

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Seasonal and interannual variability of carbon monoxide based on MOZAIC observations, MACC reanalysis, and model simulations over an urban site in India

et al. 2014

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In the lower troposphere, the CO mixing ratio showed strong seasonality, with higher levels (>300 ppbv) during the winter and premonsoon seasons associated with a stable anticyclonic circulation, while lower CO values (up to 100 ppbv) were observed in the monsoon season. In the planetary boundary layer (PBL), the seasonal distribution of CO shows the impact of both local meteorology and emissions. While the PBL CO is predominantly influenced by strong winds, bringing regional background air from marine and biomass burning regions, under calm conditions CO levels are elevated by local emissions. On the other hand, in the free troposphere, seasonal variation reflects the impact of long-range transport associated with the Intertropical Convergence Zone and biomass burning. The interannual variations were mainly due to transition from El Niño to La Niña conditions. The overall modified normalized mean biases (normalization based on the observed and model mean values) with respect to the observed CO profiles were lower for the MACC reanalysis than the MOZART and MRI-CCM2 models. The CO in the PBL region was consistently underestimated by MACC reanalysis during all the seasons, while MOZART and MRI-CCM2 show both positive and negative biases depending on the season.

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Performance evaluation of chemistry transport models over India

Cited by 66 publications

References 72 publications

The impact of residential combustion emissions on atmospheric aerosol, human health, and climate

The impact of residential combustion emissions on atmospheric aerosol, human health, and climate

Trends in aerosol optical depth over Indian region: Potential causes and impact indicators

Seasonal and interannual variability of carbon monoxide based on MOZAIC observations, MACC reanalysis, and model simulations over an urban site in India

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