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Background: The rapid emergence of coronary artery disease (CAD) in south Asian people is not explained by conventional risk factors. In view of cardioprotective effects of a Mediterranean style diet rich in alpha-linolenic acid, we assessed the benefits of this diet for patients at high risk of CAD.
Methods: We did a randomised, single-blind trial in 1000 patients with angina pectoris, myocardial infarction, or surrogate risk factors for CAD. 499 patients were allocated to a diet rich in whole grains, fruits, vegetables, walnuts, and almonds. 501 controls consumed a local diet similar to the step I National Cholesterol Education Program (NCEP) prudent diet.
Interpretation: An Indo-Mediterranean diet that is rich in alpha-linolenic acid might be more effective in primary and secondary prevention of CAD than the conventional step I NCEP prudent diet.
How dangerous are these frequent border disputes and standoffs, whether they begin as spontaneous patrol clashes, infrastructure building projects, or, as prominent scholar of South Asian security Ashley Tellis has recently argued, as more carefully planned attempts to amend the political map in the Himalayas?
Climate, too, poses unusual challenges for military operations. While the summer weather in Ladakh is pleasant enough for tourist camping, winter lows in the minus 10s and 20s Fahrenheit are not uncommon, and high winds are frequent. Winter temperatures bring the threat of frostbite and hypothermia-related attrition of forces, and even render some equipment useless as lubricants freeze and barrels on tubed artillery may crack. In eastern sectors of the border, different climate challenges complicate military operations: The monsoon rains in Arunachal Pradesh (some of the heaviest in the world) regularly cause landslides that cut lines of communication and render troop movement impossible.
Aidan Milliff is a PhD candidate in the MIT Department of Political Science and an affiliate of the MIT Security Studies Program and the Lakshmi Mittal and Family South Asia Institute at Harvard. His research focuses on behavior and decision-making during violence, emotions and in political violence, and South Asian security.
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A thorough understanding of the dynamics, evolution, fate and human influence on atmospheric CO2 is essential to enact effective carbon mitigation policies. The spatial and temporal variations of atmospheric CO2 show distinct annual, seasonal and latitudinal gradients15. There are substantial differences in CO2 concentrations between continents and oceans, which are dependent on the sources of emissions. Large-scale atmospheric circulations, weather systems and jet streams distribute CO2 around the globe15. Northern Hemisphere (NH) is known for higher levels of atmospheric CO2 than that of the Southern Hemisphere (SH). In NH, seasonal changes in CO2 are primarily driven by the result of metabolic activity of terrestrial plants and soils16. The warmer climate alters the seasonal CO2 cycle17. The effect of rising atmospheric CO2 increases radiative forcing, which leads to higher sea surface temperature (SST)18. These also cause a reduction in surface-to-deep ocean transport of CO2 and a reduction in oceanic carbon, which might increase the concentration of atmospheric CO219.
An oceanic region enclosed by 28 C or higher SST isotherm is known as a warm pool20. These are the regions with high precipitation, strong atmospheric convection and surface wind convergence21. The warm pool regions of western tropical Pacific Ocean and the tropical Indian Ocean constitute the Indo-Pacific Warm Pool (IPWP)22. Previous studies suggest that warmer SST in IPWP strengthens the upwelling branch of Hadley circulation and weakens (strengthens) its downwelling branch in NH (SH). Furthermore, due to the rapid warming of Indian Ocean, the westward extension of IPWP shifts the walker circulation westward, which decreases subsidence over eastern Africa and makes the region drier23,24.
IPWP has a significant role in transporting surface emissions to higher altitudes over the tropics. Such a system, which is a source of heat and moisture, prevails throughout the year regardless of seasons in West Pacific and East Indian Ocean (EIO) in the tropics. IPWP shows meridional and zonal variability that can influence global atmospheric circulation, and onset, intensity and duration of climate modes such as El Nio Southern Oscillation (ENSO)25. As compared to the oscillations of the eastern edge of western Pacific Warm Pool (WPWP), it is observed that South and North Warm Tongues are dominated by the annual SST cycles and are influenced by the El Nio onset, but East Cold SST Tongue is totally dominated by the El Nio onset and shows no distinct annual cycle26. Yan et al.27 studied the temperature and size variations of WPWP, and found that changes in solar irradiance, ENSO events and global warming could have modified the distribution of SST and the size of IPWP. The warm pool in Indian Ocean has a stronger annual cycle than that of Pacific28. Furthermore, SST in Indian Ocean is rising at a faster rate than in other tropical ocean regions29,30.
This study is organized as follows: we analyze the anomalously high values of mid-tropospheric CO2 over IPWP using satellite data. We examine possible reasons for the high CO2 region and its radiative forcing. We also investigate the influence of ENSO on the CO2 concentrations in the mid-troposphere. We supplement our analysis using buoy measurements to assess changes in near-surface CO2, which has a critical role in contributing to the high CO2 region.
The regional temperature exhibits a positive feedback on the atmospheric concentrations of CO2. A major region of heat source in the ocean, the IPWP, acts as a medium to distribute CO2 in the atmosphere to different altitudes12. The global distribution of SST is shown in Fig. 1b.
Liu et al.39 showed high CO2 emissions during El Nio events due to associated fire activities in south Asia. However, the ENSO composites of the detrended, deseasonalized and latitude-averaged vertical velocity (Supplementary Figure S5) reveal that its negative anomaly (downward motion of air) inhibits the upward transport of high CO2 concentration at R1 and thus, make lower CO2 in mid-troposphere there. Similarly, positive anomalies of vertical velocities are present over R1 during La Nia events. This upward-moving air transports high CO2 to the mid-troposphere from the surface, which gives rise to positive anomaly of CO2 over IPWP during strong La Nia events (Fig. 4d). As compared to R1, a contrasting effect is present over R2 owing to the opposite influence of vertical velocity during the La Nia and El Nio events.
The yearly averaged distribution of CO2 and SST show high values across the western central Indian Ocean that extends to the southeast Arabian Sea13. The region where the warm pool lies is also under the influence of ENSO events (Fig. 4a, c). The response of atmospheric CO2 to the ENSO events is identified using the averaged data of respective months (Fig. 4b, d). For instance, the positive SST anomaly over R1 during La Nia corresponds to relatively higher CO2 and the negative SST anomaly reciprocates with lower CO2 in the mid-troposphere. Similarly, the response of R2 to La Nia and El Nio reiterates the positive relationship between SST and CO2 anomalies. Furthermore, the northeast Atlantic Ocean also has a similar response, which replicates R1; indicating the influence of climate modes on SST and CO2 in all oceanic regions.
We have also considered the atmospheric and surface seawater partial pressure of CO2 (pCO2) measured by the open ocean moored buoys. ΔpCO2 is calculated by subtracting atmospheric pCO2 from surface seawater pCO2. We have combined ΔpCO2 from Tropical Atmosphere Ocean (TAO) mooring at 0, 165 E54, TAO at 8 S, 165 E55, Chuuk K1 mooring at 7.46 N, 151.90 E56 and TAO at 0, 170 W57 to represent the western Pacific, whereas Stratus at 85 W, 20 S58, TAO at 0, 110 W59 and TAO at 0, 125 W60, TAO at 0, 140 W61 to represent the eastern Pacific based on the mooring locations. Monthly averaged CO2 data from the Mauna Loa is also used to supplement the satellite data62. It is detrended and deseasonalized based on the method described by Seabold and Perktold52.
AIRS CO2 data is publicly available and can be downloaded from The ERA5 data is acquired from the Copernicus Climate Change Service Information 2020 ( -reanalysis. HadISST data are available at the website of Met Office Hadley Centre ( ). Moored buoy CO2 observations are available at Mauna Loa measurements are obtained from
The authors would like to thank the Director, Indian Institute of Technology Kharagpur, and the Chairman, Centre for Ocean, River, Atmosphere and Land Sciences (CORAL), Indian Institute of Technology Kharagpur, for providing the facilities and encouraging us to carry out this research. RP acknowledges the support from the Ministry of Education (MoE) for his Ph.D. fellowship. SN acknowledges support from NPOL, Kochi through NEMO project. We extend our gratitude to all the data providers for the datasets used in this study. This is INCOIS contribution number 488.
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