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Author Kumar, V.; Jana, S.; Bhardwaj, A.; Deepa, R.; Sahu, S.K.; Pradhan, P.K.; Sirdas, S.A.
Title Greenhouse Gas Emission, Rainfall and Crop Production Over North-Western India Type $loc['typeJournal Article']
Year 2018 Publication The Open Ecology Journal Abbreviated Journal TOECOLJ
Volume 11 Issue 1 Pages 47-61
Keywords Greenhouse gases, CH4, Climate Variability, Emissions, Crop production, Rainfall.
Abstract Background:

This study is based on datasets acquired from multi sources e.g. rain-gauges, satellite, reanalysis and coupled model for the region of Northwestern India. The influence of rainfall on crop production is obvious and direct. With the climate change and global warming, greenhouse gases are also showing an adverse impact on crop production. Greenhouse gases (e.g. CO2, NO2 and CH4) have shown an increasing trend over Northwestern Indian region. In recent years, rainfall has also shown an increasing trend over Northwestern India, while the production of rice and maize are reducing over the region. From eight selected sites, over Northwestern India, where rice and maize productions have reduced by 40%, with an increase in CO2, NO2 and CH4 gas emission by 5% from 1998 to 2011.

Results:

The correlation from one year to another between rainfall, gas emission and crop production was not very robust throughout the study period, but seemed to be stronger for some years than others.

Conclusion:

Such trends and crop yield are attributed to rainfall, greenhouse gas emissions and to the climate variability.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1874-2130 ISBN Medium
Area Expedition Conference
Funding Approved $loc['no']
Call Number COAPS @ user @ Serial 1017
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Author Liu, M.; Lin, J.; Wang, Y.; Sun, Y.; Zheng, B.; Shao, J.; Chen, L.; Zheng, Y.; Chen, J.; Fu, T.-M.; Yan, Y.; Zhang, Q.; Wu, Z.
Title Spatiotemporal variability of NO2 and PM2.5 over Eastern China: observational and model analyses with a novel statistical method Type $loc['typeJournal Article']
Year 2018 Publication Atmospheric Chemistry and Physics Abbreviated Journal Atmos. Chem. Phys.
Volume 18 Issue 17 Pages 12933-12952
Keywords TROPOSPHERIC NITROGEN-DIOXIDE; PROVINCIAL CAPITAL CITIES; CRITERIA AIR-POLLUTANTS; BOUNDARY-LAYER; NORTH CHINA; HILBERT SPECTRUM; UNITED-STATES; TIME-SERIES; OZONE; EMISSIONS
Abstract Eastern China (27-41 degrees N, 110-123 degrees E) is heavily polluted by nitrogen dioxide (NO2), particulate matter with aerodynamic diameter below 2.5 mu m (PM2.5), and other air pollutants. These pollutants vary on a variety of temporal and spatial scales, with many temporal scales that are nonperiodic and nonstationary, challenging proper quantitative characterization and visualization. This study uses a newly compiled EOF-EEMD analysis visualization package to evaluate the spatiotemporal variability of ground-level NO2, PM2.5, and their associations with meteorological processes over Eastern China in fall-winter 2013. Applying the package to observed hourly pollutant data reveals a primary spatial pattern representing Eastern China synchronous variation in time, which is dominated by diurnal variability with a much weaker day-to-day signal. A secondary spatial mode, representing north-south opposing changes in time with no constant period, is characterized by wind-related dilution or a buildup of pollutants from one day to another.

We further evaluate simulations of nested GEOS-Chem v9-02 and WRF/CMAQ v5.0.1 in capturing the spatiotemporal variability of pollutants. GEOS-Chem underestimates NO2 by about 17 mu g m(-3) and PM2.5 by 35 mu g m(-3 )on average over fall-winter 2013. It reproduces the diurnal variability for both pollutants. For the day-to-day variation, GEOS-Chem reproduces the observed north-south contrasting mode for both pollutants but not the Eastern China synchronous mode (especially for NO2). The model errors are due to a first model layer too thick (about 130 m) to capture the near-surface vertical gradient, deficiencies in the nighttime nitrogen chemistry in the first layer, and missing secondary organic aerosols and anthropogenic dust. CMAQ overestimates the diurnal cycle of pollutants due to too-weak boundary layer mixing, especially in the nighttime, and overestimates NO2 by about 30 mu g m(-3) and PM2.5 by 60 mu g m(-3). For the day-to-day variability, CMAQ reproduces the observed Eastern China synchronous mode but not the north-south opposing mode of NO2. Both models capture the day-to-day variability of PM2.5 better than that of NO2. These results shed light on model improvement. The EOF-EEMD package is freely available for noncommercial uses.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1680-7324 ISBN Medium
Area Expedition Conference
Funding Approved $loc['no']
Call Number COAPS @ user @ Serial 946
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