• Clean Air & Sustainable Mobility

Ozone, dust major pollution concerns for Delhi in summer

Following Delhi government's announcement that it will prepare an action plan to deal with high pollution from April to September, experts emphasised that summer pollution has different characteristics than winter. During summer, ozone and dust are among the main sources of pollution. Particulate pollution in the season rises due to arid conditions, high heat and transportation of dust to Delhi. Experts said ozone is produced from complex interaction between nitrogen oxides (NOx) and volatile organic compounds (VOCs) that are emitted from vehicles, power plants, factories and other combustion sources and undergo cyclic reactions in the presence of sunlight to generate ground-level ozone. Track the pollution level in your city Anumita Roychowdhury, executive director, research and advocacy, Centre for Science and Environment (CSE), said, "Summer strategy will require action to control both particulate matter and gases, including NOx and ozone. During summer, ozone standards are exceeded on more days. This demands stronger action on vehicles, industries and other combustion sources." A CSE analysis in 2022 stated that every year, ground-level ozone usually exceeds the safety standard on all days of summer in some locations in Delhi-NCR. In 2022, the spatial spread, i.e., the number of stations exceeding the standard across the city, was much higher. On an average, 16 stations exceeded the standard daily in March and April last year, a 33% increase from the same time period the previous year. delhi_pollution Gufran Beig, founder project director, System of Air Quality and Weather Forecasting and Research (SAFAR), the forecasting body under the Union ministry of earth sciences, said, "As the temperature soars and crosses 39-40 degrees Celsius, ozone pollution will increase significantly in Delhi. It is mainly because the VOC emissions will increase, which helps in ozone production. Particulate matter no longer remains a lead pollutant during this period." A national assessment by CSE done on summer pollution in 2022 found that north India suffered the maximum pollution, with Delhi-NCR a hotspot. The PM2.5 average of NCR was almost three times the average of cities in southern India. The summer average PM2.5 for north India stood at 71 micrograms per cubic metre, the highest among all regions. Within north India, Delhi NCR was found to be the most polluted sub-region. Delhi ranked eighth in the country with a season average of 97 micrograms per cubic metre.

• Urban Lab

Ozone emerges as lead air pollutant in Delhi

Ground-level ozone (O3) has started to emerge as Delhi’s lead pollutant during the day regularly over the last few days, particularly after good spells of rain, according to data from the Central Pollution Control Board (CPCB). The presence of ozone has prevented Delhi’s air from touching the “good” category during this period. CPCB data over the last three weeks (from March 17 to April 6) showed that out of the 21 days, ozone was Delhi’s lead or prominent pollutant on eight days, indicating its concentration was higher than the usual pollutants which are PM 2.5 and PM 10. On March 31, when Delhi recorded its lowest 24-hour average AQI for the year at 73, it was still “satisfactory”, with both O3 and carbon monoxide (CO) emerging as the day’s prominent pollutants. The day after, when Delhi’s AQI rose to 106 (moderate), O3 was the sole lead pollutant. Most recently, O3 was also the prominent pollutant alongside PM 2.5 on April 4, when Delhi’s AQI was 109 (moderate). Meanwhile, PM 2.5 and PM 10 emerged as the prominent pollutants on days when the 24-hour average AQI was high, for instance on April 3, when it was 179 (moderate), or March 24, when it was 205 (poor). The highly reactive gas is not emitted from any direct source but gets formed in the air when oxides of nitrogen (NOx) combine with other reactive gases. This happens particularly when temperatures are high and direct sunlight is available. Owing to its reactive nature, the gas has 1-hour and 8-hour standards compared to particulate matter (PM) which has a 24-hour standard, because even a short term exposure to the gas can worsen respiratory conditions. These standards are prescribed by the CPCB. Experts said that while ozone levels remain fairly high throughout the year, its concentration starts to rise from March onwards with levels breaching the safe limit on most days between March and June. Though ozone is present in winter as well, the levels are lower owing to low temperatures, as it needs sharp sun to aid its formation. “The data shows that when pollution levels are high, we have particulate matter (PM), which is a concern. However, the background emissions of other gases like O3 and CO are still fairly high. After a spell of rain, there is a washout effect where PM settles down and we really begin to see the impact of these gases,” said Anumita Roychowdhury, executive director, research and advocacy, Centre for Science and Environment (CSE). She said that to achieve clean or good air, a multi-pollutant strategy is required that tackles gases as well and most action plans in Delhi-NCR currently focus on PM alone. “Only once we move beyond particulate matter can we achieve cleaner air, as these gases continue to remain a problem. Ozone in particular does not have a direct source, so we first need to tackle NOx and we can indirectly control ozone formation too.” An AQI of 50 or lower is classified as “good” by the CPCB, between 51 to 100 is “satisfactory”, between 101 and 200 is “moderate”, between 201 and 300 is “poor”, between 301 and 400 is “very poor” and over 400 is “severe”. CSE had also analysed Delhi’s ozone levels in March and April 2022 where they found that, on average, 16 air quality monitoring stations were exceeding the O3 norms in Delhi-NCR on a daily basis. The 1-hour limit for O3 in Delhi is 180 micrograms (mcg) per cubic metre (pcm), while the 8-hour limit is 100 mcg pcm. HT looked at the Delhi Pollution Control Committee’s (DPCC) real-time air pollution data and found that since April 1, the highest 1-hour O3 value at Dr Karni Singh Shooting Range was 190.8 mcg pcm on April 3. The highest 8-hour O3 value at the same station was 100.3 mcg pcm on April 5, which is almost at par with the safe standard. However, the highest value recorded in Delhi over this period was at Nehru Nagar, where the hourly ozone readings touched 320 mcg pcm on April 2, while the 8-hour average peaked at 131.6 mcg pcm on April 5. The average O3 levels also saw a 33% rise in 2022 compared to the corresponding period from 2021. The analysis also found that neighbourhoods in south and New Delhi districts were the most affected. “Dr K S Shooting Range in south Delhi is the most chronically affected in Delhi-NCR. This is followed by JLN Stadium, RK Puram and Nehru Nagar in New Delhi,” CSE said in its analysis in June 2022. Professor Mukesh Khare from the department of civil engineering at IIT Delhi said while PM 2.5 has been considered a pollutant based on which most policies and pollution-mitigation strategies have been designed in the last decade, it is now time to focus on other pollutants too, particularly different gases. “We need to control oxides of nitrogen first which emanate from vehicles and industries. CO is a combustion source that is equally dangerous. While we know the impact PM 2.5 has on human health, both CO and O3 can cause dangerous, respiratory problems and even suffocation in an open environment,” said Prof Khare.

• Climate Change and Green Economy

Quantifying the role of antecedent Southwestern Indian Ocean capacitance on the summer monsoon rainfall variability over homogeneous regions of India

Download PDF Download PDF Article Open Access Published: 05 April 2023 Quantifying the role of antecedent Southwestern Indian Ocean capacitance on the summer monsoon rainfall variability over homogeneous regions of India Venugopal Thandlam, Hasibur Rahaman, …S. S. V. S. Ramakrishna Show authors Scientific Reports volume 13, Article number: 5553 (2023) Cite this article 2 Altmetric Metricsdetails Abstract The role of ocean variability is at a focal point in improving the weather and climate forecasts at different spatial and temporal scales. We study the effect of antecedent southwestern Indian Ocean mean sea level anomaly (MSLA) and sea surface temperature anomalies (SSTA) as a proxy to upper ocean heat capacitance on all India summer monsoon rainfall (AISMR) during 1993–2019. SSTA and MSLA over the southwestern Indian Ocean (SWIO) have been influenced by El Niño-Southern Oscillation (ENSO), the impact of ENSO-induced SWIO variability was low on rainfall variability over several homogeneous regions. Rainfall over northeast (NE) and North India (EI) has been modulated by ENSO-induced SSTA and MSLA over SWIO, thus effecting the total AISMR magnitude. The ENSO-induced changes in heat capacitance (SSTA and MSLA) over SWIO during antecedent months has less impact on west coast of India, central India and North India (NI) rainfall variability. The long-term trend in pre-monsoonal SSTA and MSLA over SWIO shows decreasing rainfall trend over NI, NE, and EI in the recent time. Furthermore, the cooler (warmer) anomaly over the western Indian Ocean affects rainfall variability adversely (favourably) due to the reversal of the wind pattern during the pre-monsoon period. While SSTA and MSLA are increasing in the SWIO, large-scale variability of these parameters during preceding winter and pre-monsoon months combined with surface winds could impact the inter-annual AISMR variability over homogeneous regions of India. Similarly, from an oceanic perspective, the antecedent heat capacitance over SWIO on an inter-annual time scale has been the key to the extreme monsoon rainfall variability. Introduction The Asian monsoon circulation influences most of the tropics and subtropics of the eastern hemisphere and more than 60% of the Earth’s population1,2. Monsoon variations, mainly unanticipated, impart significant economic and social damages and consequences. It’s failure often brings famine to affected regions, and strong monsoon years can result in devastating floods3. Meanwhile, recent rapid changes in the global climate and warming temperatures increase the demand for local and regional weather forecasting and analysis to improve the accuracy of seasonal forecasting of extreme events such as droughts and floods. An accurate long-range seasonal and intra-seasonal predictions of monsoon rainfall can improve planning to act on monsoon’s adverse impacts and benefits1,4. Hence, a better understanding of the monsoon cycle is clearly of scientific and social value. Yet, all India summer monsoon rainfall (AISMR) variability on the inter-annual and intraseasonal time scale has puzzled the scientific community due to its complex and regional heterogenity5,6. With innovative technological advancement and many years of research, most dynamical and statistical models still fail to predict the seasonal and intraseasonal AISMR variability and associated extremes with reasonable accuracy7,8,9. This could be due to the unpredictable variability within the AISMR and the lack of understanding of the ocean’s role in AISMR variability. This implies that the persistent ambiguity on the impact of the slowly responding ocean surface to the extreme atmosphere–ocean coupled phenomena such as El Niño-Southern Oscillation (ENSO) during the antecedent months and its imprint on the rainfall variability of the following year10,11,12. Many previous studies have shown the role of ENSO in the Indian Ocean and on seasonal AISMR. But it’s the effect on different parts of the Indian mainland i,e., homogeneous regions, has not been examined yet. Hence, this study focused on addressing this aspect. Download PDF Download PDF Article Open Access Published: 05 April 2023 Quantifying the role of antecedent Southwestern Indian Ocean capacitance on the summer monsoon rainfall variability over homogeneous regions of India Venugopal Thandlam, Hasibur Rahaman, …S. S. V. S. Ramakrishna Show authors Scientific Reports volume 13, Article number: 5553 (2023) Cite this article 2 Altmetric Metricsdetails Abstract The role of ocean variability is at a focal point in improving the weather and climate forecasts at different spatial and temporal scales. We study the effect of antecedent southwestern Indian Ocean mean sea level anomaly (MSLA) and sea surface temperature anomalies (SSTA) as a proxy to upper ocean heat capacitance on all India summer monsoon rainfall (AISMR) during 1993–2019. SSTA and MSLA over the southwestern Indian Ocean (SWIO) have been influenced by El Niño-Southern Oscillation (ENSO), the impact of ENSO-induced SWIO variability was low on rainfall variability over several homogeneous regions. Rainfall over northeast (NE) and North India (EI) has been modulated by ENSO-induced SSTA and MSLA over SWIO, thus effecting the total AISMR magnitude. The ENSO-induced changes in heat capacitance (SSTA and MSLA) over SWIO during antecedent months has less impact on west coast of India, central India and North India (NI) rainfall variability. The long-term trend in pre-monsoonal SSTA and MSLA over SWIO shows decreasing rainfall trend over NI, NE, and EI in the recent time. Furthermore, the cooler (warmer) anomaly over the western Indian Ocean affects rainfall variability adversely (favourably) due to the reversal of the wind pattern during the pre-monsoon period. While SSTA and MSLA are increasing in the SWIO, large-scale variability of these parameters during preceding winter and pre-monsoon months combined with surface winds could impact the inter-annual AISMR variability over homogeneous regions of India. Similarly, from an oceanic perspective, the antecedent heat capacitance over SWIO on an inter-annual time scale has been the key to the extreme monsoon rainfall variability. Introduction The Asian monsoon circulation influences most of the tropics and subtropics of the eastern hemisphere and more than 60% of the Earth’s population1,2. Monsoon variations, mainly unanticipated, impart significant economic and social damages and consequences. It’s failure often brings famine to affected regions, and strong monsoon years can result in devastating floods3. Meanwhile, recent rapid changes in the global climate and warming temperatures increase the demand for local and regional weather forecasting and analysis to improve the accuracy of seasonal forecasting of extreme events such as droughts and floods. An accurate long-range seasonal and intra-seasonal predictions of monsoon rainfall can improve planning to act on monsoon’s adverse impacts and benefits1,4. Hence, a better understanding of the monsoon cycle is clearly of scientific and social value. Yet, all India summer monsoon rainfall (AISMR) variability on the inter-annual and intraseasonal time scale has puzzled the scientific community due to its complex and regional heterogenity5,6. With innovative technological advancement and many years of research, most dynamical and statistical models still fail to predict the seasonal and intraseasonal AISMR variability and associated extremes with reasonable accuracy7,8,9. This could be due to the unpredictable variability within the AISMR and the lack of understanding of the ocean’s role in AISMR variability. This implies that the persistent ambiguity on the impact of the slowly responding ocean surface to the extreme atmosphere–ocean coupled phenomena such as El Niño-Southern Oscillation (ENSO) during the antecedent months and its imprint on the rainfall variability of the following year10,11,12. Many previous studies have shown the role of ENSO in the Indian Ocean and on seasonal AISMR. But it’s the effect on different parts of the Indian mainland i,e., homogeneous regions, has not been examined yet. Hence, this study focused on addressing this aspect. Blanford13 was the first to attempt a forecast of the seasonal AISMR following the disastrous famine of 1877. The study was based on the hypotheses that the varying extent and thickness of the Himalayan snow exercise a tremendous and prolonged influence on the climatic conditions and weather of the plains of northwest India13. Since then, much research has been done on predicting AISMR14,15,16,17,18. Shukla19 suggested that colder sea surface temperature anomalies (SSTA) over the western Arabian Sea and Somali coast may cause a reduction in AISMR over India and adjoining areas. AISMR is significantly positively correlated with Indian Ocean SSTA and moisture flux transport in the preceding winter and spring seasons on the time scale of the Tropical Biennial Oscillation20. Several empirical studies show a strong positive correlation of Arabian Sea SSTA averaged over March, April, and May with AISMR21,22,23. Harzallah and Sadourny24 investigated the lag-lead relationships of global SSTA and the AISMR Index from 1950 to 90. In the fall and winter preceding a strong monsoon, they found positive SSTA in the Indian Ocean, especially in the Arabian Sea. Vecchi and Harisson25 have shown that warm SSTA over the western Arabian Sea at the AISMR onset is associated with increased Western Ghat rainfall along the west coast of India, while cool SSTA off Java and Sumatra is associated with increased precipitation over the Ganges-Mahanadi basin. AISMR also has a significant and positive correlation with latent heat and momentum flux induced by SSTA during antecedent winter over the Arabian Sea, Bay of Bengal, and the South China Sea26. Many other studies also highlighted the positive correlations between pre-monsoon months’ SSTA over the western Arabian Sea and the southwestern Indian Ocean (SWIO)27 during AISMR28,29,30,31. Kothawale et al.27,32 have found that November SSTA over the Arabian Sea, Bay of Bengal, and equatorial South Indian Ocean is strongly correlated with AISMR during 1971–2002. Out of five homogeneous regions in India, monsoon rainfall over the West Coast of India (WCI) showed a significant relationship with Arabian SSTA of the preceding spring and winter months32. At the same time, Bay of Bengal SSTA in the preceding November and March and equatorial South Indian Ocean SSTAs of the preceding November, February, and March showed a substantial impact on WCI rainfall variability20,33. Thus, many past studies concentrated only on relationships between pre-monsoon SSTA over the Indian Ocean region and AISMR seasonal variability and forecasting28,29,30,31. As the AISMR is a coupled atmosphere–ocean phenomenon, the role of air-sea interactions over the southwestern and equatorial Indian Ocean is the key to the better understanding and forecasting of its magnitude and variability over India34,35,36. Shankar and Shetye37 have suggested that the interdecadal variability of sea level at Mumbai mimicked the variability in rainfall over the Indian subcontinent. Similarly, ocean mean temperature, representing the upper ocean heat energy over the SWIO during pre-monsoon months of the same year, shows a strong statistical relationship with the AISMR34. Venugopal et al.35 statistically illustrated that ocean mean temperature during January, February, and March over the SWIO could be a better ocean parameter for AISMR seasonal forecasting and variability during normal synoptic conditions. Thus, a few studies have focused on the relationship between sea level variations and subsurface ocean variability over the Indian Ocean region and AISMR34,35. Some of these studies stressed the use of new statistical techniques and parameters, such as the strength of the winds, ocean heat content and ocean-integrated subsurface temperatures in the seasonal forecasting35,36. Distinct impacts of short- and long-time fluctuations of the Indian Ocean surface wind fields, particularly over the SWIO, also led to changes in the rainfall over homogeneous regions of India38. Monthly, seasonal, and regional rainfall intensities contribute to the total magnitude of annual AISMR. But rainfall during July–August contributes to the total extent of seasonal rain, regardless of the strength (strong or weak) of the summer monsoon39. The strength of the monsoon and intraseasonal variability (MISO) depends on the prevailing synoptic conditions and intraseasonal variability of atmospheric and ocean parameters over the tropics, particularly in the tropical Indian and Pacific Oceans40,41,42,43,44. Recently Saha et al.45 have shown that the synoptic variability, previously considered as noise, is predictable and has maximum contribution to the seasonal AISMR anomaly. Therefore, AISMR is a highly predictable system on a seasonal time scale. These synoptic activities and MISO, which are smaller in magnitude and affect the intensity of rainfall, are found to be associated with the planetary scale circulations like Madden–Julian Oscillation (MJO), ENSO, Indian Ocean Dipole, Pacific Decadal Oscillation and North Atlantic Oscillation46,47,48,49,50,51. Thus, the predictability of AISMR also lies on the planetary scale events, which evolve on a longer time scale and may leave their signature and impacts on the smaller-scale events to persist for a longer time45. Though several studies found a relationship between summer monsoon and the upper ocean parameters over the SWIO concerning preceding months of the same year, none has focused on the relationship between rainfall over homogeneous regions of the Indian landmass and the SWIO. The question here is, does the Indian Ocean variability affect the entire Indian mainland AISMR or not? and how does the ENSO would impact this relationship? To the best of our knowledge, no studies are available as of now about how the Indian Ocean variability impacts the different sub-divisions of India, popularly known as homogeneous regions. The high ocean heat capacitance could hold the signature of planetary-scale events to persist for an extended period, thus impacting the synoptic conditions in the following years. Hence, studying the role of antecedent upper ocean capacitance over the SWIO on AISMR and other homogeneous regions with and without the impact of planetary-scale events like ENSO could provide more insights into the influence of the air-sea interactions on synoptic conditions over this region. Furthermore, exploring the effect of the SWIO capacitance on homogeneous rainfall regions of India could give a more localized glance at physical processes and altering air-sea interactions due to recent climate change over these regions leading to changes in the frequencies and intensities of extreme floods and droughts52,53. Also, quantifying the set of atmospheric and ocean parameters in seasonal numerical weather forecasting systems such as ECMWF’s new long-range forecasting system SEAS5 is a high priority to improve the forecast precision. Yet, a wide range of conflicting results can be found describing the relationship between Indian Ocean SSTA and Indian continental rainfall anomalies, which may partly arise because of uncertainties in our knowledge of Indian Ocean SSTA25. Much of the Indian Ocean was not well observed during the last century either by satellite observations or automated profiling floats such as ARGO. There were only observations from ships and drifting buoys54,55. Many studies have noted that the statistical relationship between monsoon variability and upper ocean parameters can be different in recent decades than in earlier decades3,56,57,58. The advent of satellite altimetry and microwave techniques to measure sea level anomaly (SLA) and SSTA, respectively, have provided data sets with better spatial and temporal coverage over the Indian Ocean region and contributed to the betterment of this statistical relationship in recent times. On the other hand, sub-surface temperature and salinity profile data from scattered XBT, CTD, ARGO, and buoy locations were previously available with spatial and temporal sampling errors. However, ARGO has recently made revolutions in this aspect by measuring temperature/salinity (T/S) profile data since 2001 over the global ocean, including the Indian Ocean from 200359,60. Although the spatial distribution pattern of ARGO profiling floats was sparse during the initial phase, it has reached its objective to have at least one profile in a 3 × 3-degree domain in 2008 over the global ocean, including the Indian Ocean61. The other most reliable subsurface information comes from the sea level measurement since it shows the mirror image of subsurface variation on the surface. This data has been available from satellite altimetry with high spatial resolutions since 1992. In this study, we use these high spatial resolution datasets during 1993–2019 to determine the relationship between AISMR and MSLA and SSTA before and after removing the Nino3.4 SSTA effect. A robust and distinct relationship with these parameters in the Indian Ocean has been found in recent years, especially after 200129. We examined the role of these parameters over the SWIO in the rainfall variability of different homogeneous regions of India. “Data” section describes the datasets used, and “Methodology” section describes the methodology adopted in the study. Subsequently, “Results and discussions” section describes the results and discussions. Finally, the conclusions are summarized in “Climatic effect of the Indian Ocean on AISMR” section. Download PDF Download PDF Article Open Access Published: 05 April 2023 Quantifying the role of antecedent Southwestern Indian Ocean capacitance on the summer monsoon rainfall variability over homogeneous regions of India Venugopal Thandlam, Hasibur Rahaman, …S. S. V. S. Ramakrishna Show authors Scientific Reports volume 13, Article number: 5553 (2023) Cite this article 2 Altmetric Metricsdetails Abstract The role of ocean variability is at a focal point in improving the weather and climate forecasts at different spatial and temporal scales. We study the effect of antecedent southwestern Indian Ocean mean sea level anomaly (MSLA) and sea surface temperature anomalies (SSTA) as a proxy to upper ocean heat capacitance on all India summer monsoon rainfall (AISMR) during 1993–2019. SSTA and MSLA over the southwestern Indian Ocean (SWIO) have been influenced by El Niño-Southern Oscillation (ENSO), the impact of ENSO-induced SWIO variability was low on rainfall variability over several homogeneous regions. Rainfall over northeast (NE) and North India (EI) has been modulated by ENSO-induced SSTA and MSLA over SWIO, thus effecting the total AISMR magnitude. The ENSO-induced changes in heat capacitance (SSTA and MSLA) over SWIO during antecedent months has less impact on west coast of India, central India and North India (NI) rainfall variability. The long-term trend in pre-monsoonal SSTA and MSLA over SWIO shows decreasing rainfall trend over NI, NE, and EI in the recent time. Furthermore, the cooler (warmer) anomaly over the western Indian Ocean affects rainfall variability adversely (favourably) due to the reversal of the wind pattern during the pre-monsoon period. While SSTA and MSLA are increasing in the SWIO, large-scale variability of these parameters during preceding winter and pre-monsoon months combined with surface winds could impact the inter-annual AISMR variability over homogeneous regions of India. Similarly, from an oceanic perspective, the antecedent heat capacitance over SWIO on an inter-annual time scale has been the key to the extreme monsoon rainfall variability. Introduction The Asian monsoon circulation influences most of the tropics and subtropics of the eastern hemisphere and more than 60% of the Earth’s population1,2. Monsoon variations, mainly unanticipated, impart significant economic and social damages and consequences. It’s failure often brings famine to affected regions, and strong monsoon years can result in devastating floods3. Meanwhile, recent rapid changes in the global climate and warming temperatures increase the demand for local and regional weather forecasting and analysis to improve the accuracy of seasonal forecasting of extreme events such as droughts and floods. An accurate long-range seasonal and intra-seasonal predictions of monsoon rainfall can improve planning to act on monsoon’s adverse impacts and benefits1,4. Hence, a better understanding of the monsoon cycle is clearly of scientific and social value. Yet, all India summer monsoon rainfall (AISMR) variability on the inter-annual and intraseasonal time scale has puzzled the scientific community due to its complex and regional heterogenity5,6. With innovative technological advancement and many years of research, most dynamical and statistical models still fail to predict the seasonal and intraseasonal AISMR variability and associated extremes with reasonable accuracy7,8,9. This could be due to the unpredictable variability within the AISMR and the lack of understanding of the ocean’s role in AISMR variability. This implies that the persistent ambiguity on the impact of the slowly responding ocean surface to the extreme atmosphere–ocean coupled phenomena such as El Niño-Southern Oscillation (ENSO) during the antecedent months and its imprint on the rainfall variability of the following year10,11,12. Many previous studies have shown the role of ENSO in the Indian Ocean and on seasonal AISMR. But it’s the effect on different parts of the Indian mainland i,e., homogeneous regions, has not been examined yet. Hence, this study focused on addressing this aspect. Blanford13 was the first to attempt a forecast of the seasonal AISMR following the disastrous famine of 1877. The study was based on the hypotheses that the varying extent and thickness of the Himalayan snow exercise a tremendous and prolonged influence on the climatic conditions and weather of the plains of northwest India13. Since then, much research has been done on predicting AISMR14,15,16,17,18. Shukla19 suggested that colder sea surface temperature anomalies (SSTA) over the western Arabian Sea and Somali coast may cause a reduction in AISMR over India and adjoining areas. AISMR is significantly positively correlated with Indian Ocean SSTA and moisture flux transport in the preceding winter and spring seasons on the time scale of the Tropical Biennial Oscillation20. Several empirical studies show a strong positive correlation of Arabian Sea SSTA averaged over March, April, and May with AISMR21,22,23. Harzallah and Sadourny24 investigated the lag-lead relationships of global SSTA and the AISMR Index from 1950 to 90. In the fall and winter preceding a strong monsoon, they found positive SSTA in the Indian Ocean, especially in the Arabian Sea. Vecchi and Harisson25 have shown that warm SSTA over the western Arabian Sea at the AISMR onset is associated with increased Western Ghat rainfall along the west coast of India, while cool SSTA off Java and Sumatra is associated with increased precipitation over the Ganges-Mahanadi basin. AISMR also has a significant and positive correlation with latent heat and momentum flux induced by SSTA during antecedent winter over the Arabian Sea, Bay of Bengal, and the South China Sea26. Many other studies also highlighted the positive correlations between pre-monsoon months’ SSTA over the western Arabian Sea and the southwestern Indian Ocean (SWIO)27 during AISMR28,29,30,31. Kothawale et al.27,32 have found that November SSTA over the Arabian Sea, Bay of Bengal, and equatorial South Indian Ocean is strongly correlated with AISMR during 1971–2002. Out of five homogeneous regions in India, monsoon rainfall over the West Coast of India (WCI) showed a significant relationship with Arabian SSTA of the preceding spring and winter months32. At the same time, Bay of Bengal SSTA in the preceding November and March and equatorial South Indian Ocean SSTAs of the preceding November, February, and March showed a substantial impact on WCI rainfall variability20,33. Thus, many past studies concentrated only on relationships between pre-monsoon SSTA over the Indian Ocean region and AISMR seasonal variability and forecasting28,29,30,31. As the AISMR is a coupled atmosphere–ocean phenomenon, the role of air-sea interactions over the southwestern and equatorial Indian Ocean is the key to the better understanding and forecasting of its magnitude and variability over India34,35,36. Shankar and Shetye37 have suggested that the interdecadal variability of sea level at Mumbai mimicked the variability in rainfall over the Indian subcontinent. Similarly, ocean mean temperature, representing the upper ocean heat energy over the SWIO during pre-monsoon months of the same year, shows a strong statistical relationship with the AISMR34. Venugopal et al.35 statistically illustrated that ocean mean temperature during January, February, and March over the SWIO could be a better ocean parameter for AISMR seasonal forecasting and variability during normal synoptic conditions. Thus, a few studies have focused on the relationship between sea level variations and subsurface ocean variability over the Indian Ocean region and AISMR34,35. Some of these studies stressed the use of new statistical techniques and parameters, such as the strength of the winds, ocean heat content and ocean-integrated subsurface temperatures in the seasonal forecasting35,36. Distinct impacts of short- and long-time fluctuations of the Indian Ocean surface wind fields, particularly over the SWIO, also led to changes in the rainfall over homogeneous regions of India38. Monthly, seasonal, and regional rainfall intensities contribute to the total magnitude of annual AISMR. But rainfall during July–August contributes to the total extent of seasonal rain, regardless of the strength (strong or weak) of the summer monsoon39. The strength of the monsoon and intraseasonal variability (MISO) depends on the prevailing synoptic conditions and intraseasonal variability of atmospheric and ocean parameters over the tropics, particularly in the tropical Indian and Pacific Oceans40,41,42,43,44. Recently Saha et al.45 have shown that the synoptic variability, previously considered as noise, is predictable and has maximum contribution to the seasonal AISMR anomaly. Therefore, AISMR is a highly predictable system on a seasonal time scale. These synoptic activities and MISO, which are smaller in magnitude and affect the intensity of rainfall, are found to be associated with the planetary scale circulations like Madden–Julian Oscillation (MJO), ENSO, Indian Ocean Dipole, Pacific Decadal Oscillation and North Atlantic Oscillation46,47,48,49,50,51. Thus, the predictability of AISMR also lies on the planetary scale events, which evolve on a longer time scale and may leave their signature and impacts on the smaller-scale events to persist for a longer time45. Though several studies found a relationship between summer monsoon and the upper ocean parameters over the SWIO concerning preceding months of the same year, none has focused on the relationship between rainfall over homogeneous regions of the Indian landmass and the SWIO. The question here is, does the Indian Ocean variability affect the entire Indian mainland AISMR or not? and how does the ENSO would impact this relationship? To the best of our knowledge, no studies are available as of now about how the Indian Ocean variability impacts the different sub-divisions of India, popularly known as homogeneous regions. The high ocean heat capacitance could hold the signature of planetary-scale events to persist for an extended period, thus impacting the synoptic conditions in the following years. Hence, studying the role of antecedent upper ocean capacitance over the SWIO on AISMR and other homogeneous regions with and without the impact of planetary-scale events like ENSO could provide more insights into the influence of the air-sea interactions on synoptic conditions over this region. Furthermore, exploring the effect of the SWIO capacitance on homogeneous rainfall regions of India could give a more localized glance at physical processes and altering air-sea interactions due to recent climate change over these regions leading to changes in the frequencies and intensities of extreme floods and droughts52,53. Also, quantifying the set of atmospheric and ocean parameters in seasonal numerical weather forecasting systems such as ECMWF’s new long-range forecasting system SEAS5 is a high priority to improve the forecast precision. Yet, a wide range of conflicting results can be found describing the relationship between Indian Ocean SSTA and Indian continental rainfall anomalies, which may partly arise because of uncertainties in our knowledge of Indian Ocean SSTA25. Much of the Indian Ocean was not well observed during the last century either by satellite observations or automated profiling floats such as ARGO. There were only observations from ships and drifting buoys54,55. Many studies have noted that the statistical relationship between monsoon variability and upper ocean parameters can be different in recent decades than in earlier decades3,56,57,58. The advent of satellite altimetry and microwave techniques to measure sea level anomaly (SLA) and SSTA, respectively, have provided data sets with better spatial and temporal coverage over the Indian Ocean region and contributed to the betterment of this statistical relationship in recent times. On the other hand, sub-surface temperature and salinity profile data from scattered XBT, CTD, ARGO, and buoy locations were previously available with spatial and temporal sampling errors. However, ARGO has recently made revolutions in this aspect by measuring temperature/salinity (T/S) profile data since 2001 over the global ocean, including the Indian Ocean from 200359,60. Although the spatial distribution pattern of ARGO profiling floats was sparse during the initial phase, it has reached its objective to have at least one profile in a 3 × 3-degree domain in 2008 over the global ocean, including the Indian Ocean61. The other most reliable subsurface information comes from the sea level measurement since it shows the mirror image of subsurface variation on the surface. This data has been available from satellite altimetry with high spatial resolutions since 1992. In this study, we use these high spatial resolution datasets during 1993–2019 to determine the relationship between AISMR and MSLA and SSTA before and after removing the Nino3.4 SSTA effect. A robust and distinct relationship with these parameters in the Indian Ocean has been found in recent years, especially after 200129. We examined the role of these parameters over the SWIO in the rainfall variability of different homogeneous regions of India. “Data” section describes the datasets used, and “Methodology” section describes the methodology adopted in the study. Subsequently, “Results and discussions” section describes the results and discussions. Finally, the conclusions are summarized in “Climatic effect of the Indian Ocean on AISMR” section. Data The high-resolution (0.25 × 0.25) blended analysis of daily Optimum Interpolation SST (OISSTv2.1, also known as Reynolds’ SST) obtained from the National Oceanic and Atmospheric Administration (NOAA) during 1993–201962 has been used in the study. In addition, we used delayed-time (reprocessed) daily sea level anomalies (SLA) data for the 1993–2019 period with a spatial resolution of 0.25°, obtained from Copernicus Marine Environment Monitoring Service (CMEMS)63. This product is obtained by combining fully processed data from various altimeter missions (Topex/Poseidon, ERS-1/2, Jason-1, Envisat and OSTM/Jason-2). The daily AISMR data has been extracted from the high-resolution (0.25 × 0.25) daily rainfall data constructed from more than 7000 rain gauge stations around India during the study period64,65. The AISMR data used in the study show a lower seasonal magnitude of rainfall than the data from Rajeevan et al.65,which has the 1° × 1° resolution (Figure not shown). The bias could be due to the annual changes in the number of rain gauge stations used in constructing the data. Despite its lower magnitude, the dataset has been used in the study owing to its higher spatial resolution and our aim of studying the rainfall variability rather the magnitude. Based on the rainfall intensity and variability, homogeneous regions of AISMR are broadly divided into north India (NI), east India (EI), northeast India (NE), central India (CI), and WCI37,66. More details on selected regions are provided in Table 1. Similarly, the Nino3.4 (170° W–120° W and 5° S–5° N) region’s monthly SSTA indices for ENSO were obtained from the Royal Netherlands Meteorological Institute climate explorer67. In addition, monthly surface zonal and meridional wind anomalies constructed from ECMWF-ERA5 with the 0.25 × 0.25-degree resolution have been used in the composite analysis68. Tabl Sharma, U. Book review: Sunita Narain, Shazneen Cyrus Gazdar, Avantika Goswami, and Tarun Gopalakrishnan (edited by Souparno Banerjee). 2021. Climate Change: Science and Politics. Contrib. Indian Sociol. 55, 475–479 (2021).

• Urban Lab

Winter pollution worst in Asansol, least in Haldia

KOLKATA: Asansol was the most and Haldia the least polluted township in Bengal this winter, the latest analysis by Centre for Science and Environment revealed. Smaller towns among eastern states recorded higher pollution than usual this winter, when Bengal recorded the highest pollution since '19-'20, the study showed. Asansol, with 102 g/m³ winter average of PM2.5, turned out to be the most polluted township, followed by Howrah (92 g/m³). Talcher (75 g/m³) was the most polluted in Odisha. At 46 g/m³ winter average of PM2.5, Haldia in Bengal was the least polluted township among the three states, followed by Siliguri (60 g/m³) here and Manguraha in Bihar (66 g/m³). "The analysis indicates the rapid spread of pollution. More townships are scaling the pollution height. This vindicates the need for state-wide as well as regional management of pollution. We need to check local pollution sources, like vehicles, industry, open burning and construction dust, as well as the impact of upwind pollution sources on downwind cities and towns," said Anumita Roychowhdury, executive director, (research and advocacy), CSE. Avikal Somvanshi, senior programme manager, Urban Lab, CSE pointed out the challenge of data collection in smaller towns. "Though real-time monitoring has increased in the region, including in Jharkhand, some data could not be used due to gaps and quality issues. Some machines are new and so, long-term data is not available," Somvanshi said. Bigger cities in the region, like Kolkata, which is part of National Clean Air Programme), saw a slight improvement in the winter average of PM2.5 levels than that of previous two winters, but their levels were still high. Overall, Bengal's peak winter average PM2.5 this year was 14% higher than that of last winter, Bihar's rise was 26% and Odisha's 44%.

• Urban Lab

CPCB report bares Kolkata’s toxic winter air between October 1 and February 28

The level of the most toxic air pollutant, PM 2.5, in Kolkata during the just concluded winter was more than 30 per cent higher than the national limit. Around 40 per cent of the winter days had either very poor or poor air, shows an air pollution report released on Tuesday. According to the Union environment ministry, “very poor” air “affects healthy people and seriously impacts those with existing diseases”. “Poor” air may lead to “respiratory illness on prolonged exposure”. The report — Winter Air Pollution Trends: East India — was prepared by environment think tank Centre for Science and Environment (CSE). It is based on real-time PM 2.5 data generated by the Central Pollution Control Board (CPCB) between October 1 and February 28. PM 2.5 refers to ultrafine particulates, which are the most potent air pollutants as they can penetrate deep into the lungs and trigger a host of critical ailments. Kolkata’s average PM 2.5 concentration during the 2022-23 winter was 80 microgram per cubic metre of air. In the previous winter, it was 79 microgram. The national limit is 60 microgram. West Bengal’s average PM 2.5 concentration during the 2022-23 winter was 84 microgram. Asansol was the most polluted city in the state, having recorded an average PM 2.5 concentration of 102 microgram. Haldia, another industrial city, recorded an average PM 2.5 concentration of 46 microgram and emerged as the least polluted city. “Kolkata had 26 very poor air quality days during the winter while the similar statistic was 12 in the 2021-22 winter months. Overall 64 days during the 2022-23 winter were either very poor or poor in terms of air quality in Kolkata; together consisting over two-fifth of the winter days,” says the report. The analysis shows that Kolkata’s highest PM 2.5 value for a day during the winter was 151 microgram, 2.5 times above the national limit. The corresponding figure in the previous winter was 150 microgram. In eastern India, Bihar was found to be the most polluted state with Begusarai being the most polluted city with an average PM 2.5 concentration of 275 microgram, 450 per cent above normal. “The winter pollution level in Kolkata this season has been seven per cent lower than the mean of previous three winters but is still considerably higher than the standard,” said Anumita Roy Chowdhury, air pollution expert from CSE. Roy Choudhury further said: “AQI (air quality index) categorisation of days shows that… the number of days with poor and very poor air quality has increased this winter compared to last year. However, it has not been as bad as winter of 2020-21.” Abhijit Chatterjee, an air pollution expert with Bose Institute, said: “Clearly, the emission reduction in the city has reached a plateau. Unless we immediately start to cut down emission from major sources like solid waste and biomass burning, along with vehicular pollution and construction, it will be almost impossible to achieve significant improvement.” Chatterjee said that along with macro actions, there was a need for micro-level actions and decentralised air pollution monitoring and control in the city.

• Urban Lab

WINTER AIR POLLUTION TRENDS: EAST INDIA

pollution this winter – says CSE’s latest analysis West Bengal, Bihar and Odisha experience most polluted winter season since 2019-20 Even though the long term trend in winter air quality improved marginally over the last three years, it worsened compared to the previous year’s winter in most cities Patna in Bihar had the highest increase in winter pollution this winter among the major cities Pollution levels worst in smaller towns of Bihar Peak winter pollution dangerously high in all eastern states Beginnings of a multi-pollutant crisis noted in the region with high nitrogen dioxide levels in early winter More action needed to control pollution from vehicles, industry, open burning, landfill fires, use of solid fuels in households, construction dust and other area sources For the complete state-wise analysis: https://www.cseindia.org/APC-Winter-air-pollution-EAST-INDIA-NOTE-April4.pdf New Delhi, April 4, 2023: Cities in India’s eastern states are increasingly falling into the pincer grip of toxic particulate pollution during winter season – and the problem is spreading quickly to the smaller cities and towns of the region: says a latest assessment by Centre for Science and Environment (CSE) released here today. The assessment also notes that though the bigger cities in the region – like Patna and Kolkata — that are part of the National Clean Air Programme (NCAP), have witnessed a marginal improvement in the winter average of their PM2.5 levels compared to the previous two winters, their levels are still high. The smaller towns of Bihar — Begusarai, Bettiah and Siwan in particular — have recorded the worst winter air in the region, with their seasonal average exceeding 200 microgram per cubic metre (µg/m³). Nitrogen dioxide (NO2) pollution is also high in the cities and towns of the region, with Arrah in Bihar recording a staggering 113 µg/m³ monthly average for November, notes CSE. “This analysis is a stark reminder of the rapid spread of pollution. More cities and smaller towns are scaling the pollution height and dotting the pollution map. This once again vindicates the need for a strong state-wide and regional management of air pollution. This is needed to control local pollution sources including vehicles, industry, open burning and construction dust, as well as the impact of upwind pollution sources on downwind cities and towns,” says Anumita Roychowhdury, executive director, research and advocacy, CSE. “Additionally, data gap is also a challenge in the region. Even though the real time monitors have increased in the region including in Jharkhand, some of these could not be used due to data gaps and quality issues. Some of these are new and therefore long term data is not available. The data, thus, is indicative of the current status and seasonal variation in particulate pollution in medium and smaller cities,” says Avikal Somvanshi, senior programme manager, Urban Lab, CSE. With the winter season coming to an end, the Urban Lab at CSE has analysed air quality trends during the winter months (October 2022 to February 2023) in cities of the eastern states of West Bengal, Bihar and Odisha. This is an assessment of seasonal trends in PM2.5 concentration for the period October 1, 2022 to February 28, 2023 for 2019, 2020, 2021, 2022 and 2023. Winter inversion and cool and calm conditions trap local pollution that is already high. This is part of the third edition of the Urban Lab’s Air Quality Tracker Initiative since 2020-21. This analysis covers 50 continuous ambient air quality monitoring stations (CAAQMS) spread across 32 cities in the three states: West Bengal: seven stations in Kolkata, three in Howrah, and one each in Asansol, Siliguri, Durgapur and Haldia. Real time monitors in Durgapur and Haldia became operational only by the end of 2020. Bihar: Six stations in Patna, three each in Gaya and Muzaffarpur, two in Bhagalpur, and one each in Hajipur, Bettiah, Bihar Sharif, Darbhanga, Motihari, Araria, Arrah, Chhapra, Katihar, Kishanganj, Manguraha, Munger, Purnia, Rajgir, Saharsa, Sasaram, Siwan, Aurangabad, Begusarai and Samastipur Odisha: One real time station each in Talcher and Brajrajnagar. Many new stations have been added in November 2022 — one station each in Baripada, Bileipada, Keonjhar, Nayagarh, Rairangpur, Rourkela, Suakati and Tensa. Only a limited long term trend analysis has been possible for the cities that have added stations and monitors relatively recently (like some of the cities in Odisha). Jharkhand has no working monitoring stations, and hence, offers no PM2.5 data for the last two years – which is why its cities have not been included in this analysis. This analysis is based on the real time data available from the current working air quality monitoring stations in east India. Somvanshi says a huge volume of data points have been cleaned and data gaps addressed based on the United States Environmental Protection Agency (USEPA) method for this analysis. Key findings of the CSE analysis Eastern states have experienced the most polluted winter season since 2019-20: The average PM2.5 level across nine cities of east India with functional CAAQMS stations since 2019 stood at 97 µg/m³ this winter. The PM2.5 level was 6 per cent higher compared to the average of previous three winters. The daily peak of the season was recorded on January 1, 2023 and the daily regional average stood at 173 µg/m³. The peak was 24 per cent higher compared to the peak of 2021-22 winter and 8 per cent higher compared to the mean peak of previous three winters. Most cities have experienced worsening of winter PM2.5 levels: West Bengal’s winter average PM2.5 this year is 14 per cent higher than that in the previous winter. Bihar registered a 26 per cent rise, and Odisha a 44 per cent higher winter average compared to the previous winter. On a long term basis, Bihar registered an 18 per cent increase and Odisha a 4 per cent increase from the mean level of previous three winters. However, the seasonal air quality in West Bengal this winter is 4 per cent better than the mean of previous three winters. In absolute concentration terms, Bihar with an average PM2.5 level of 134 µg/m³ was the most polluted state in the east, followed by West Bengal with average PM2.5 level of 84 µg/m³; Odisha was third with a seasonal average of 63 µg/m³. Peak pollution is dangerously high in all eastern states: In absolute concentration terms, Bihar’s daily peak PM2.5 level of 287 µg/m³ was the highest among the three states. West Bengal’s peak was 152 µg/m³ and Odisha’s, 112 µg/m³. In the long term, the seasonal peak in West Bengal this winter has been 1 per cent better than the mean of previous three winter peaks. Bihar registered a 26 per cent increase and Odisha a 14 per cent increase in their peaks compared to the mean of previous three winter peaks. Smaller cities of Bihar are most polluted in the region: Begusarai was the most polluted city in the east with an average PM2.5 level of 275 µg/m³. It was followed by Siwan with 203 µg/m³, Bettiah (202 µg/m³), Katihar (188 µg/m³), and Saharsa (180 µg/m³). All the top 20 most polluted cities of the east are located in Bihar. In West Bengal, Asansol, with a winter average of 102 µg/m³ was the most polluted city; it is followed by Howrah (92 µg/m³) at the second spot. Talcher (75 µg/m³) was the most polluted in Odisha – however, adds Somvanshi, “since only two cities in the state have real time monitors with adequate data for assessment, it is not possible to capture the larger landscape.” Haldia in West Bengal was the least polluted city among the three states with a PM2.5 average of 46 µg/m³, followed by Siliguri in West Bengal and Manguraha in Bihar with winter averages of 60 µg/m³ and 66 µg/m³, respectively. Patna registered the highest increase in winter pollution this winter among the major cities in the region: Patna in Bihar and Talcher in Odisha were the worst performers and registered an increase of 39 per cent and 41 per cent from the previous year, respectively. These were followed by Asansol in West Bengal and Gaya in Bihar, which recorded an increase of 38 per cent and 37 per cent, respectively. Howrah (0 per cent), Kolkata (3 per cent) and Muzaffarpur (8 per cent) registered nil to marginal increases in pollution levels this season compared to the previous winter. Haldia and Durgapur are the only two cities that have shown improvement in air quality this season compared to the corresponding period in the previous year. Durgapur registered the maximum improvement — 30 per cent lower PM2.5 levels compared to the previous year; Haldia clocked a 19 per cent dip. Increasing levels of NO2 in November: There was a significant increase in NO2 concentrations during November compared to the months of October and September. NO2 comes entirely from combustion sources and significantly, from vehicles. Patna registered the greatest increase — 2.9 times — with the maximum build-up of NO2 between September and November 2022. Katihar and Rajgir each registered a 2.6 times increase in NO2. Motihari, Kolkata and Howrah registered a 2.3 times hike. In absolute concentration terms, Arrah in Bihar registered the highest NO2 average of 113 µg/m³ (see Graph in the detailed report). It is followed by Bhagalpur with 98 µg/m³ and Siwan with 89 µg/m³. Among West Bengal cities, Asansol with a monthly average of 40 µg/m³ was the most polluted. Diwali pollution was the highest in the small towns of Bihar among the eastern states: The Diwali of this winter was less polluted compared to the previous year’s Diwali for all the major cities in the region. However, the smaller cities of Bihar witnessed the maximum increase in pollution levels on Diwali night. In fact, pollution level on Diwali night (8 pm to 8 am) shot up by 0.2-2.3 times the average level recorded during the seven nights preceding Diwali. Nine out of 32 stations recorded an increase in pollution on the day of Diwali. Motihari in Bihar saw the greatest jump of 2.3-times higher PM2.5 level — 152 µg/m³ — on Diwali night. It was followed by Siwan and Bettiah each with 1.8-times higher PM2.5 concentrations. Bihar cities dominate the top 15 list of cities with the most polluted Diwali nights. Among West Bengal cities, Asansol recorded a Diwali night PM2.5 level of 42 µg/m³. Haldia and Manguraha each with 12 µg/m³ had the least polluted Diwali night in the region, followed by Durgapur with 13 µg/m³. Step up the action Says Roychowdhury: “High winter pollution is an indicator of a deeper and rapid spread of air pollution in the eastern region. As the winter turns hostile due to inversion and cold and calm conditions, pollution gets trapped and spirals. This requires an aggressive strategy to control pollution not only in the bigger cities, but also across the region to mitigate pollution from vehicles and transportation, industries, open burning of waste, landfill fires, construction, household use of solid fuels, and other area sources. It is necessary to reduce pollution in a targeted manner to meet the clean air standards.”

• Urban Lab

Bihar, West Bengal, and Odisha face severe pollution in winter: CSE Report

In a recent report by the Center for Science and Environment, winter pollution in the eastern states of India was worse this year compared to the last three winters.

• DTE-Hindi

रिकॉर्ड स्तर पर पहुंचा क्लोरोफ्लोरोकार्बन, ओजोन को कर सकता है कमजोर

धरती को सूर्य से बचाने वाली ओजोन परत को कमजोर करने वाली क्लोरोफ्लोरोकार्बन पर दुनिया भर में प्रतिबंध लगा दिया गया था, लेकिन वैज्ञानिकों ने खुलासा किया कि कुछ मानव निर्मित क्लोरोफ्लोरोकार्बन रिकॉर्ड स्तर तक पहुंच गई है। जलवायु में बदलाव करने वाला यह उत्सर्जन लगातार बढ़ रहा है। अध्ययन के अनुसार, मॉन्ट्रियल प्रोटोकॉल के तहत प्रतिबंधित होने के बावजूद, पांच क्लोरोफ्लोरोकार्बन (सीएफसी) 2010 से 2020 तक वातावरण में तेजी से बढ़ गए, जो 2020 में रिकॉर्ड-उच्च स्तर तक पहुंच गए। डाउन टू अर्थ Search रिकॉर्ड स्तर पर पहुंचा क्लोरोफ्लोरोकार्बन, ओजोन को कर सकता है कमजोर सीएफसी शक्तिशाली ग्रीनहाउस गैसें हैं जो कार्बन डाइऑक्साइड की तुलना में 10 हजार गुना अधिक तेजी से गर्मी को फंसाते हैं, यही ग्लोबल वार्मिंग का सबसे बड़ा कारण है जो जलवायु में बदलाव के लिए जिम्मेवार है By Dayanidhi On: Tuesday 04 April 2023 अगली खबर ❯ ओजोन को कमजोर करने वाली सीएफसी पर प्रतिबंध के बावजूद रिकॉर्ड स्तर: अध्ययनफोटो साभार : विकिमीडिया कॉमन्स, सुयश द्विवेदी फोटो साभार : विकिमीडिया कॉमन्स, सुयश द्विवेदी धरती को सूर्य से बचाने वाली ओजोन परत को कमजोर करने वाली क्लोरोफ्लोरोकार्बन पर दुनिया भर में प्रतिबंध लगा दिया गया था, लेकिन वैज्ञानिकों ने खुलासा किया कि कुछ मानव निर्मित क्लोरोफ्लोरोकार्बन रिकॉर्ड स्तर तक पहुंच गई है। जलवायु में बदलाव करने वाला यह उत्सर्जन लगातार बढ़ रहा है। अध्ययन के अनुसार, मॉन्ट्रियल प्रोटोकॉल के तहत प्रतिबंधित होने के बावजूद, पांच क्लोरोफ्लोरोकार्बन (सीएफसी) 2010 से 2020 तक वातावरण में तेजी से बढ़ गए, जो 2020 में रिकॉर्ड-उच्च स्तर तक पहुंच गए। Why I quit the corporate world to start teaching mud house construction अध्ययन में कहा गया है कि यह वृद्धि शायद हाइड्रोफ्लोरोकार्बन (एचएफओ) सहित सीएफसी को बदलने के लिए बने रसायनों के उत्पादन के दौरान रिसाव के कारण हुआ था। हालांकि मौजूदा स्तरों पर वे ओजोन परत की बहाली के लिए खतरा नहीं हैं, वे वातावरण को गर्म करने वाले अन्य उत्सर्जन में शामिल होकर एक अलग खतरे को बढ़ा सकते हैं। सह-अध्ययनकर्ता इसहाक विमोंट ने कहा, यदि आप इन अगली पीढ़ी के यौगिकों के उत्पादन के दौरान ग्रीनहाउस गैसों और ओजोन को कमजोर करने वाले पदार्थों का उत्पादन कर रहे हैं, तो उनका जलवायु और ओजोन परत पर अप्रत्यक्ष प्रभाव पड़ता है। विमोंट, अमेरिका के नेशनल ओशनिक एंड एटमॉस्फेरिक एडमिनिस्ट्रेशन में ग्लोबल मॉनिटरिंग लेबोरेटरी में शोधकर्ता है। ग्लोबल कार्बन प्रोजेक्ट के आंकड़ों के मुताबिक, सीएफसी शक्तिशाली ग्रीनहाउस गैसें हैं जो कार्बन डाइऑक्साइड की तुलना में 10 हजार गुना अधिक तेजी से गर्मी को फंसाते हैं, यही ग्लोबल वार्मिंग का सबसे बड़ा कारण है जो जलवायु में बदलाव के लिए जिम्मेवार है। 1970 से 1980 के दशक में, सीएफसी का ठंडा करने के लिए और एयरोसोल स्प्रे में उपयोग किया जाता था। लेकिन इसके उपयोग के कारण अंटार्कटिका के ऊपर ओजोन परत में छेद का पता चला, जिसके बाद सीएफसी को प्रतिबंधित करने के लिए 1987 में वैश्विक समझौता किया गया। इस समझौते को मॉन्ट्रियल प्रोटोकॉल के नाम से जाना जाता है, इसके लागू होने के बाद, दुनिया भर में सीएफसी की मात्रा में लगातार गिरावट देखी गई। ओजोन का कमजोर पड़ना एक शुरुआती चेतावनी अध्ययन ने 2010 में दुनिया भर से इसको खत्म करने या वैश्विक फेज-आउट के बिंदु से शुरुआत करते हुए या कुछ वर्तमान में उपयोग की जाने वाले पांच सीएफसी का विश्लेषण किया। ब्रिस्टल यूनिवर्सिटी और ग्लोबल मॉनिटरिंग लेबोरेटरी के सह-अध्ययनकर्ता ल्यूक वेस्टर्न ने कहा कि उन उत्सर्जनों का अब तक ओजोन परत पर मामूली प्रभाव पड़ा है और थोड़ा अधिक प्रभाव जलवायु पर पड़ा है। वे स्विट्जरलैंड के 2020 में सीओ2 उत्सर्जन के बराबर हैं, यह अमेरिका के कुल ग्रीनहाउस गैस उत्सर्जन का लगभग एक प्रतिशत के बराबर है। अध्ययन के मुताबिक प्रत्यक्ष माप शुरू होने के बाद से 2020 में सीएफसी की सभी पांचों गैसें अपनी उच्चतम स्तर पर थीं। लेकिन अगर इसी तरह तेजी जारी रहती है, तो उनका प्रभाव बढ़ जाएगा। शोधकर्ताओं ने अपने निष्कर्षों को एक नए तरीके की शुरुआती चेतावनी कहा जिसमें सीएफसी ओजोन परत को खतरे में डाल रहे हैं। उत्सर्जन के उन प्रक्रियाओं के कारण होने की आशंका है जो वर्तमान में प्रतिबंध और अप्रतिबंधित उपयोगों के अधीन नहीं हैं। मॉन्ट्रियल प्रोटोकॉल द्वारा प्रतिबंधित, उनको बदलने के लिए विकसित औद्योगिक एरोसोल की श्रेणी को अगले तीन दशकों में 1987 की संधि के हालिया संशोधन के तहत चरणबद्ध तरीके से समाप्त किया जाना है। सीएफसी के अज्ञात स्रोत प्रोटोकॉल ओजोन को कमजोर करने वाले पदार्थों के निकलने पर अंकुश लगाता है जो वातावरण में फैल सकते हैं, लेकिन कच्चे माल या उप-उत्पादों के रूप में अन्य रसायनों के उत्पादन में उनके उपयोग पर प्रतिबंध नहीं लगाते हैं। यह पहली बार नहीं था कि अघोषित उत्पादन का सीएफसी स्तरों पर प्रभाव पड़ा। 2018 में वैज्ञानिकों ने पाया कि सीएफसी की गति पिछले पांच वर्षों की तुलना में आधी हो गई थी। शोधकर्ताओं ने कहा कि उस मामले में साक्ष्य पूर्वी चीन में कारखानों की ओर इशारा करते हैं। एक बार जब उस क्षेत्र में सीएफसी का उत्पादन बंद हो गया, तो यह वापस पटरी पर आ गया। अध्ययन में कहा गया है कि सीएफसी उत्सर्जन में हालिया वृद्धि के सटीक स्रोत को जानने के लिए और शोध की आवश्यकता है। राष्ट्रव्यापी आंकड़ों की कमी के चलते यह निर्धारित करना मुश्किल हैं कि गैसें कहां से आ रही हैं और विश्लेषण किए गए कुछ सीएफसी के उपयोग के बारे में जानकारी नहीं है। वेस्टर्न ने कहा लेकिन ग्रीनहाउस गैस उत्सर्जन को कम करने के मामले में इन उत्सर्जन को खत्म करना एक आसान जीत है। यह अध्ययन नेचर जियोसाइंस नामक पत्रिका में प्रकाशित हुआ है।

• Urban Lab

Smaller Towns In Bihar, Bengal And Odisha Record Higher Pollution This Winter: CSE Analysis

The CSE's analysis revealed that cities in West Bengal, Bihar, and Odisha are increasingly falling victim to toxic particulate pollution during winter. Newsclick SUBSCRIBE AND SUPPORT Search DropDownMenu Smaller Towns in Eastern India Record Higher Pollution in Winter: Report Mohd. Imran Khan | 04 Apr 2023 Environment Politics India The CSE's analysis revealed that cities in West Bengal, Bihar, and Odisha are increasingly falling victim to toxic particulate pollution during winter. Representational Image. Image Courtesy: Pexels Representational Image. Image Courtesy: PTI Patna: Smaller towns in eastern Indian states experienced higher levels of pollution during the winter season of 2022-23, according to the latest air quality analysis by the Centre for Science and Environment (CSE), a non-profit organisation based in New Delhi. The CSE's analysis, released on Tuesday, revealed that cities in West Bengal, Bihar, and Odisha are increasingly falling victim to toxic particulate pollution during winter, with the problem spreading rapidly to smaller cities and towns in the region. The assessment also pointed out that though the bigger cities in the region – like Patna and Kolkata -- that are part of the National Clean Air Programme (NCAP) have witnessed a marginal improvement in the winter average of their PM2.5 levels compared to the previous two winters, their levels are still high. The smaller towns of Bihar -- Begusarai, Bettiah and Siwan in particular -- have recorded the worst winter air in the region, with their seasonal average exceeding 200 micrograms per cubic metre (µg/m³). Nitrogen dioxide (NO2) pollution is also high in the cities and towns of the region, with Arrah in Bihar recording a staggering 113 µg/m³ monthly average for November, the report said. “This analysis is a stark reminder of the rapid spread of pollution. More cities and smaller towns are scaling the pollution height and dotting the pollution map. This once again vindicates the need for strong state-wide and regional management of air pollution. This is needed to control local pollution sources, including vehicles, industry, open burning and construction dust, as well as the impact of upwind pollution sources on downwind cities and towns,” said Anumita Roychowhdury, executive director of Research and Advocacy, CSE, in a press release. This analysis covers 50 continuous ambient air quality monitoring stations (CAAQMS) spread across 32 cities in the three eastern states. The CSE’s study highlighted that the eastern states experienced the most polluted winter season since 2019-20. The average PM2.5 level across nine cities of east India with functional CAAQMS stations stood at 97 µg/m³ this winter. The PM2.5 level was 6% higher compared to the average of the previous three winters. The daily peak of the season was recorded on January 1, 2023, and the daily regional average stood at 173 µg/m³. The peak was 24% higher compared to the 2021-22 winter peak and 8% higher compared to the mean peak of the previous three winters. Most cities have experienced worsening of winter PM2.5 levels: West Bengal’s winter average PM2.5 this year is 14% higher than the previous winter. Bihar registered a 26% and Odisha a 44% increase in the winter average compared to the previous one, the report said. On a long-term basis, Bihar registered an 18% and Odisha a 4% rise from the mean level of the previous three winters. However, the seasonal air quality in West Bengal this winter is 4% better than the mean of the last three winters. In absolute concentration terms, Bihar, with an average PM2.5 level of 134 µg/m³, was the most polluted state in the east. It is followed by West Bengal with an average PM2.5 level of 84 µg/m³; Odisha came third with 63 µg/m³. According to CSE’s report, peak pollution is dangerously high in all eastern states: In absolute concentration terms, Bihar’s daily peak PM2.5 level of 287 µg/m³ was the highest among the three states. West Bengal’s peak was 152 µg/m³ and Odisha’s 112 µg/m³. In the long term, the seasonal peak in West Bengal this winter has been 1% better than the mean of the previous three winter peaks. Bihar registered a 26% increase, and Odisha a 14% increase in their peaks compared to the mean of the previous three winter peaks. Smaller cities of Bihar are most polluted in the region. Begusarai was the most polluted city in the east, with an average PM2.5 level of 275 µg/m³. It was followed by Siwan with 203 µg/m³, Bettiah (202 µg/m³), Katihar (188 µg/m³), and Saharsa (180 µg/m³). Notably, the top 20 most polluted cities of the east are in Bihar. In West Bengal, Asansol, with a winter average of 102 µg/m³ was the most polluted city; it is followed by Howrah (92 µg/m³) at the second spot. Talcher (75 µg/m³) was the most polluted in Odisha. However, Somvanshi added, “Since only two cities in the state have real-time monitors with adequate data for assessment, it is not possible to capture the larger landscape.” Haldia in West Bengal was the least polluted city among the three states with a PM2.5 average of 46 µg/m³, followed by Siliguri in West Bengal and Manguraha in Bihar with winter averages of 60 µg/m³ and 66 µg/m³, respectively. Among major cities in the east, Patna registered the highest increase in winter pollution this time. Patna in Bihar and Talcher in Odisha were the worst performers and registered an increase of 39% and 41% from the previous year, respectively. These were followed by Asansol in West Bengal and Gaya in Bihar, which recorded an increase of 38% and 37%, respectively. Haldia and Durgapur in West Bengal are the only two cities that have shown improvement in air quality this season compared to the corresponding period in the previous year. Durgapur registered the maximum improvement -- 30% lower PM2.5 levels compared to the previous year; Haldia clocked a 19 per cent dip. There was a significant increase in NO2 concentrations during November compared to October and September. NO2 comes entirely from combustion sources and, majorly from vehicles. Patna registered the most significant increase -- 2.9 times -- with the maximum build-up of NO2 between September and November 2022. Katihar and Rajgir each registered a 2.6 times increase in NO2. Motihari, Kolkata and Howrah registered a 2.3 times hike. In absolute concentration terms, Arrah in Bihar registered the highest NO2 average of 113 µg/m³ (see Graph in the detailed report). It is followed by Bhagalpur with 98 µg/m³ and Siwan with 89 µg/m³.

• Urban Lab

All the top 20 most polluted cities of east India located in Bihar

NEW DELHI: Cities in India’s eastern states — Bihar, West Bengal and Odisha — are increasingly falling into the pincer grip of toxic particulate pollution during winter season, and the problem is spreading quickly to the smaller cities and towns of the region, said the Centre for Science and Environment (CSE) in its latest assessment released on Tuesday. The CSE noted that even though the long-term trend in winter air quality improved marginally, it worsened last winter (2022-23) with the eastern states experiencing the most polluted season since 2019-20. In absolute concentration terms, Bihar with an average PM2.5 level of 134 micrograms per cubic meter (µg/m3) was the most polluted state in the east, followed by West Bengal with average PM2.5 level of 84 µg/m3. Odisha was third with a seasonal average of 63 µg/m3.

• Renewable Energy

संकट में विन्ड एनर्जी सेक्टर, क्या बोली का तरीका बदलने से सुधरेंगे हालात?

ग्लोबल विंड एनर्जी कॉउंसिल द्वारा जारी 2023 की ग्लोबल विंड रिपोर्ट में कहा गया है कि पवन ऊर्जा उद्योग इस साल रिकॉर्ड ऊर्जा क्षमता स्थापना की उम्मीद कर रहा है, लेकिन आपूर्ति श्रृंखला (सप्लाई चेन) में आनेवाली चुनौतियों से निपटने के लिए नीति-निर्माताओं को तत्काल कदम उठाने होंगे। रिपोर्ट के अनुसार पवन ऊर्जा के मामले में साल 2022 निराशाजनक रहा। हालांकि पिछले साल विंड पावर में विश्व-स्तर पर 78 गीगावाट (1 गीगावॉट = 1,000 मेगावॉट) की बढ़त हुई और कुल स्थापित वैश्विक क्षमता बढ़कर 906 गीगावाट हो गई। ताजा अनुमान है कि 2027 तक 680 गीगावाट नई क्षमता स्थापित की जाएगी, यानि हर साल करीब 136 गीगावाट। यदि ऐसा हुआ तो 2023 पहला वर्ष होगा जब विश्व-स्तर पर 100 गीगावाट से अधिक की नई क्षमता स्थापित होगी। विशेषज्ञ कहते हैं पवन ऊर्जा में 2030 के जलवायु संबंधी लक्ष्यों को हासिल करने में काफी मददगार हो सकते हैं और 2050 तक नेट जीरो तक पहुंचने की राह भी आसान होगी। हाल ही में संयुक्त राष्ट्र महासचिव एंटोनियो गुट्रिश ने अमीर देशों से 2040 और विकासशील देशों से 2050 तक नेट जीरो पर पहुंचने का प्रयास करने का आग्रह किया था। उन्होंने कहा था कि ग्लोबल वार्मिंग को 1.5 डिग्री सेल्सियस पर सीमित करने के लिए यह आवश्यक है। भारत की स्थिति, तय लक्ष्यों से पीछे भारत पवन ऊर्जा क्षमता के मामले में चीन, अमेरिका और जर्मनी के बाद दुनिया में चौथे नंबर पर है। नेशनल पावर पोर्टल पर उपलब्ध आंकड़ों के मुताबिक भारत की कुल पवन ऊर्जा क्षमता अभी 42,015 मेगावॉट यानी 42 गीगावॉट है। भारत ने 2022 में कुल तटवर्ती पवन ऊर्जा क्षमता में 1847 मेगावॉट की बढ़ोतरी की। साफ ऊर्जा मंत्रालय के मुताबिक भारत का लक्ष्य 2030 तक कुल 30,000 मेगावॉट के अपतटीय पवन ऊर्जा संयंत्र लगाने का है। भारत ने 2022 तक 175 गीगावाट नवीकरणीय ऊर्जा क्षमता स्थापित करने का जो लक्ष्य रखा था, उसमें सौर ऊर्जा (100 गीगावाट) के बाद सबसे बड़ा हिस्सा पवन ऊर्जा से प्राप्त होना नियोजित था — 60 गीगावाट। लेकिन जहां सौर ऊर्जा का लक्ष्य करीब 62 प्रतिशत हासिल हो पाया और पवन ऊर्जा के मामले में 2022 के अंत तक 60 की अपेक्षा लगभग 41 गीगावाट के संयंत्र ही स्थापित हो पाए। भारत पिछले कई सालों से लगातार पवन ऊर्जा लक्ष्यों को हासिल करने में नाकाम रहा है। 2019-20 में 3,000 मेगावाट की जगह 2,117 मेगावाट, जबकि 2020-21 में 3,000 मेगावाट के लक्ष्य का करीब 50 प्रतिशत — 1,503 मेगावाट — ही प्राप्त हो सका। विन्ड एनर्जी क्षेत्र के जानकार इसके लिए सरकार की नीतियों को दोष देते हैं। इंडियन विन्ड टर्बाइन मैन्युफेक्चरर्स एसोसिएशन के सेक्रेटरी जनरल डी वी गिरि ने कार्बनकॉपी हिन्दी को बताया कि भारत दुनिया में सबसे सस्ती पवनचक्कियां बनाता है और सत्तर प्रतिशत से अधिक निर्माण देश के भीतर होता है। इसके बावजूद पिछले 6 साल से विन्ड एनर्जी सेक्टर की हालात ठीक नहीं है। गिरि कहते हैं, “हमारे पास हर साल 15 गीगावॉट की पवनचक्कियां लगाने की क्षमता है। फिर भी 2017 के बाद से हम प्रतिवर्ष केवल 1.5 गीगावॉट क्षमता ही हर साल बढ़ा रहे हैं। यानी हर साल हम अपनी क्षमता का 10 प्रतिशत ही इजाफा कर पा रहे हैं। यह बिल्कुल भी स्वीकार्य नहीं है।” अक्टूबर 2015 में सरकार ने ‘राष्ट्रीय अपतटीय पवन ऊर्जा नीति‘ (नेशनल ऑफशोर विन्ड एनर्जी पॉलिसी) अधिसूचित की थी, जिसके अंतर्गत गुजरात और तमिलनाडु में आठ-आठ ज़ोन संभावित अपतटीय क्षेत्रों के रूप में चिन्हित किए गए थे। इन क्षेत्रों के भीतर 70 गीगावाट ऊर्जा क्षमता स्थापित होने का अनुमान था। लेकिन अगस्त 2022 की संसद की स्थाई समिति की रिपोर्ट बताती है कि पॉलिसी नोटिफाई के सात साल बाद भी देश में एक भी अपतटीय पवन ऊर्जा प्रोजेक्ट स्थापित नहीं हो पाया है। खरीद मूल्य का संकट, बिडिंग के तरीके पर सवाल दिल्ली स्थित सेंटर फॉर साइंस एंड इंवारेंमेंट (सीएसई) में रिन्यूएबल एनर्जी के डिप्टी प्रोग्राम मैनेजर बिनित दास कहते हैं, “भारत में एक बड़ी चुनौती पवन ऊर्जा की कीमत है। वर्तमान में रिवर्स बिडिंग प्रणाली के कारण डिस्कॉम बिजली कंपनियों से काफी कम कीमत पर विन्ड पावर खरीद रहे हैं। इससे डेवलपर हतोत्साहित हो रहे हैं और वह विन्ड एनर्जी से दूर जा रहे हैं और निवेशक इसके बजाय सोलर प्रोजेक्ट्स में पैसा लगाना चाहते हैं।” दास ने कार्बनकॉपी से कहा कि पिछले तीन सालों में हमने पवन ऊर्जा की नई संयोजन क्षमता (कैपेसिटी एडिशन) का ग्राफ गिरते देखा है। असल में भारत ने 2030 तक कुल 500 गीगावॉट साफ ऊर्जा क्षमता का लक्ष्य रखा है जिसमें 140 गीगावॉट पवन ऊर्जा होगी यानी अगले साढ़े सात सालों में भारत को 98 गीगावॉट विन्ड एनर्जी के संयंत्र लगाने हैं। इसके लिए हर साल औसतन 13 गीगावॉट से अधिक क्षमता संयोजन (पावर एडिशन) करना होगा। लेकिन अगर पवन ऊर्जा क्षमता बढ़ने की मौजूदा रफ्तार देखें तो वह 2 गीगावॉट से अधिक नहीं रही है। इस हिसाब से 2030 के लिए तय लक्ष्य हासिल करने में 50 साल लग जाएंगे। गिरि कहते हैं, “अगर आप मुझसे पूछें कि समस्या कहां है तो मैं कहूंगा कि 2017 से पहले राज्यों के द्वारा बिजली खरीदी जाती थी। राज्यों के अपने आरपीओ होते थे। हर राज्य की बिडिंग और टैरिफ होते थे। 2017 में सरकार ने ई-रिवर्स बिडिंग लागू किया और एक ही एजेंसी सोलर एनर्जी कॉर्पोरेशन को कमान थमा थी। उन्होंने खरीद के बाकी रास्ते बन्द कर दिए।” सरकार ने करीब 6 साल पहले प्रतिस्पर्धा को बढ़ाने के लिए ई-रिवर्स बिडिंग शुरू की थी। इसमें पहले सबसे कम बोली लगाने वाले के खिलाफ बाकी कंपनियों से काउंटर बिडिंग के प्रस्ताव मांगे जा सकते हैं। इंडस्ट्री का कहना है कि रिवर्स बिडिंग के कारण खरीद मूल्य इतना गिर गया कि उनके लिए काम करना व्यवहारिक नहीं रह गया। निवेशकों का कहना है कि छोटे प्लेयर इसमें बड़े खिलाड़ियों के आगे नहीं टिक पाते। रिवर्स बिडिंग से क्लोज़ बिडिंग की ओर विन्ड सेक्टर को संकट से निकालने के लिए नवीनीकरणीय ऊर्जा मंत्रालय (एमएनआरई) ने विन्ड पावर के लिए घोषित रिवर्स ऑक्शन रद्द किए हैं और 2030 तक हर साल 8 गीगावॉट की नीलामी एक चरण में बन्द लिफाफे में बोली के आधार पर करेगी। हालांकि सरकार में बोली के तरीके को बदलने को लेकर काफी खींचतान हुई है और पावर मिनिस्ट्री ने एमएनआरई के प्रस्ताव का विरोध किया लेकिन साफ ऊर्जा मंत्रालय को लगता है कि वर्तमान तरीरे से फिलहाल विन्ड पावर क्षमता नहीं बढ़ेगी। हालांकि इस फैसले से पहले एमएनआरई मंत्री आर के सिंह ने साफ कहा कि रिवर्स बिडिंग से (डिस्कॉम को) कम कीमत पर बिजली तो मिलेगी लेकिन मैं चाहता हूं कि कंपनियां संयंत्र भी लगाएं। इसका कोई मतलब नहीं है कि बिडिंग तो हो लेकिन संयंत्र न लगें। क्लोज़ एनविलेप बिडिंग में कंपनियां दो अलग अलग लिफाफों में टेक्निकल और कमर्शियल बोलियां लगाती हैं। इसमें टेक्निकल बिड में सफल होने वाली कंपनियों के बीच देखा जाता है कि किसकी कमर्शियल बोली सबसे कम कीमत की है लेकिन उसके बाद किसी तरह की नीलामी नहीं होती। दास कहते हैं, “अलग-अलग राज्यों में संसाधनों की उपलब्धता के हिसाब से बिजली खरीद की कीमत की न्यूनतम दर तय होनी चाहिए। अगर कीमत निर्धारण से पहले हालात का सही पूर्व मूल्यांकन हो और खरीद की एक न्यूनतम सीमा तय हो तो इससे डेवलपर का हौसला बढ़ेगा।”

• Urban Lab

Smaller towns in eastern states record higher pollution this winter: analysis

April 4, 2023: Cities in India’s eastern states are increasingly falling into the pincer grip of toxic particulate pollution during winter season – and the problem is spreading quickly to the smaller cities and towns of the region: says a latest assessment by Centre for Science and Environment (CSE) released here today. The assessment also notes that though the bigger cities in the region – like Patna and Kolkata — that are part of the National Clean Air Programme (NCAP), have witnessed a marginal improvement in the winter average of their PM2.5 levels compared to the previous two winters, their levels are still high. The smaller towns of Bihar — Begusarai, Bettiah and Siwan in particular — have recorded the worst winter air in the region, with their seasonal average exceeding 200 microgram per cubic metre (µg/m³). Nitrogen dioxide (NO2) pollution is also high in the cities and towns of the region, with Arrah in Bihar recording a staggering 113 µg/m³ monthly average for November, notes CSE. “This analysis is a stark reminder of the rapid spread of pollution. More cities and smaller towns are scaling the pollution height and dotting the pollution map. This once again vindicates the need for a strong state-wide and regional management of air pollution. This is needed to control local pollution sources including vehicles, industry, open burning and construction dust, as well as the impact of upwind pollution sources on downwind cities and towns,” says Anumita Roychowhdury, executive director, research and advocacy, CSE. “Additionally, data gap is also a challenge in the region. Even though the real time monitors have increased in the region including in Jharkhand, some of these could not be used due to data gaps and quality issues. Some of these are new and therefore long term data is not available. The data, thus, is indicative of the current status and seasonal variation in particulate pollution in medium and smaller cities,” says Avikal Somvanshi, senior programme manager, Urban Lab, CSE. With the winter season coming to an end, the Urban Lab at CSE has analysed air quality trends during the winter months (October 2022 to February 2023) in cities of the eastern states of West Bengal, Bihar and Odisha. This is an assessment of seasonal trends in PM2.5 concentration for the period October 1, 2022 to February 28, 2023 for 2019, 2020, 2021, 2022 and 2023. Winter inversion and cool and calm conditions trap local pollution that is already high. This is part of the third edition of the Urban Lab’s Air Quality Tracker Initiative since 2020-21. This analysis covers 50 continuous ambient air quality monitoring stations (CAAQMS) spread across 32 cities in the three states: West Bengal: seven stations in Kolkata, three in Howrah, and one each in Asansol, Siliguri, Durgapur and Haldia. Real time monitors in Durgapur and Haldia became operational only by the end of 2020. Bihar: Six stations in Patna, three each in Gaya and Muzaffarpur, two in Bhagalpur, and one each in Hajipur, Bettiah, Bihar Sharif, Darbhanga, Motihari, Araria, Arrah, Chhapra, Katihar, Kishanganj, Manguraha, Munger, Purnia, Rajgir, Saharsa, Sasaram, Siwan, Aurangabad, Begusarai and Samastipur Odisha: One real time station each in Talcher and Brajrajnagar. Many new stations have been added in November 2022 — one station each in Baripada, Bileipada, Keonjhar, Nayagarh, Rairangpur, Rourkela, Suakati and Tensa. Only a limited long term trend analysis has been possible for the cities that have added stations and monitors relatively recently (like some of the cities in Odisha). Jharkhand has no working monitoring stations, and hence, offers no PM2.5 data for the last two years – which is why its cities have not been included in this analysis. This analysis is based on the real time data available from the current working air quality monitoring stations in east India. Somvanshi says a huge volume of data points have been cleaned and data gaps addressed based on the United States Environmental Protection Agency (USEPA) method for this analysis. Key findings of the CSE analysis Eastern states have experienced the most polluted winter season since 2019-20: The average PM2.5 level across nine cities of east India with functional CAAQMS stations since 2019 stood at 97 µg/m³ this winter. The PM2.5 level was 6 per cent higher compared to the average of previous three winters. The daily peak of the season was recorded on January 1, 2023 and the daily regional average stood at 173 µg/m³. The peak was 24 per cent higher compared to the peak of 2021-22 winter and 8 per cent higher compared to the mean peak of previous three winters. Most cities have experienced worsening of winter PM2.5 levels: West Bengal’s winter average PM2.5 this year is 14 per cent higher than that in the previous winter. Bihar registered a 26 per cent rise, and Odisha a 44 per cent higher winter average compared to the previous winter. On a long term basis, Bihar registered an 18 per cent increase and Odisha a 4 per cent increase from the mean level of previous three winters. However, the seasonal air quality in West Bengal this winter is 4 per cent better than the mean of previous three winters. In absolute concentration terms, Bihar with an average PM2.5 level of 134 µg/m³ was the most polluted state in the east, followed by West Bengal with average PM2.5 level of 84 µg/m³; Odisha was third with a seasonal average of 63 µg/m³. Peak pollution is dangerously high in all eastern states: In absolute concentration terms, Bihar’s daily peak PM2.5 level of 287 µg/m³ was the highest among the three states. West Bengal’s peak was 152 µg/m³ and Odisha’s, 112 µg/m³. In the long term, the seasonal peak in West Bengal this winter has been 1 per cent better than the mean of previous three winter peaks. Bihar registered a 26 per cent increase and Odisha a 14 per cent increase in their peaks compared to the mean of previous three winter peaks. Smaller cities of Bihar are most polluted in the region: Begusarai was the most polluted city in the east with an average PM2.5 level of 275 µg/m³. It was followed by Siwan with 203 µg/m³, Bettiah (202 µg/m³), Katihar (188 µg/m³), and Saharsa (180 µg/m³). All the top 20 most polluted cities of the east are located in Bihar. In West Bengal, Asansol, with a winter average of 102 µg/m³ was the most polluted city; it is followed by Howrah (92 µg/m³) at the second spot. Talcher (75 µg/m³) was the most polluted in Odisha – however, adds Somvanshi, “since only two cities in the state have real time monitors with adequate data for assessment, it is not possible to capture the larger landscape.” Haldia in West Bengal was the least polluted city among the three states with a PM2.5 average of 46 µg/m³, followed by Siliguri in West Bengal and Manguraha in Bihar with winter averages of 60 µg/m³ and 66 µg/m³, respectively. Patna registered the highest increase in winter pollution this winter among the major cities in the region: Patna in Bihar and Talcher in Odisha were the worst performers and registered an increase of 39 per cent and 41 per cent from the previous year, respectively. These were followed by Asansol in West Bengal and Gaya in Bihar, which recorded an increase of 38 per cent and 37 per cent, respectively. Howrah (0 per cent), Kolkata (3 per cent) and Muzaffarpur (8 per cent) registered nil to marginal increases in pollution levels this season compared to the previous winter. Haldia and Durgapur are the only two cities that have shown improvement in air quality this season compared to the corresponding period in the previous year. Durgapur registered the maximum improvement — 30 per cent lower PM2.5 levels compared to the previous year; Haldia clocked a 19 per cent dip. Increasing levels of NO2 in November: There was a significant increase in NO2 concentrations during November compared to the months of October and September. NO2 comes entirely from combustion sources and significantly, from vehicles. Patna registered the greatest increase — 2.9 times — with the maximum build-up of NO2 between September and November 2022. Katihar and Rajgir each registered a 2.6 times increase in NO2. Motihari, Kolkata and Howrah registered a 2.3 times hike. In absolute concentration terms, Arrah in Bihar registered the highest NO2 average of 113 µg/m³ (see Graph in the detailed report). It is followed by Bhagalpur with 98 µg/m³ and Siwan with 89 µg/m³. Among West Bengal cities, Asansol with a monthly average of 40 µg/m³ was the most polluted. Diwali pollution was the highest in the small towns of Bihar among the eastern states: The Diwali of this winter was less polluted compared to the previous year’s Diwali for all the major cities in the region. However, the smaller cities of Bihar witnessed the maximum increase in pollution levels on Diwali night. In fact, pollution level on Diwali night (8 pm to 8 am) shot up by 0.2-2.3 times the average level recorded during the seven nights preceding Diwali. Nine out of 32 stations recorded an increase in pollution on the day of Diwali. Motihari in Bihar saw the greatest jump of 2.3-times higher PM2.5 level — 152 µg/m³ — on Diwali night. It was followed by Siwan and Bettiah each with 1.8-times higher PM2.5 concentrations. Bihar cities dominate the top 15 list of cities with the most polluted Diwali nights. Among West Bengal cities, Asansol recorded a Diwali night PM2.5 level of 42 µg/m³. Haldia and Manguraha each with 12 µg/m³ had the least polluted Diwali night in the region, followed by Durgapur with 13 µg/m³. Step up the action Says Roychowdhury: “High winter pollution is an indicator of a deeper and rapid spread of air pollution in the eastern region. As the winter turns hostile due to inversion and cold and calm conditions, pollution gets trapped and spirals. This requires an aggressive strategy to control pollution not only in the bigger cities, but also across the region to mitigate pollution from vehicles and transportation, industries, open burning of waste, landfill fires, construction, household use of solid fuels, and other area sources. It is necessary to reduce pollution in a targeted manner to meet the clean air standards.”

• Renewable Energy

Delhi fails to make hay while sun shines

While targeting 6,000 MW from solar power by 2025, of which 750 would be from rooftop installations, Delhi, however, managed to add only 20MW of additional power in the past year through rooftop and ground solar generation. To meet the 2025 target, increased from 2,000MW recently, the capital will have to harness more than 230MW every month.Since only 9% of the power being consumed by the city currently comes from the sun, Delhi’s journey to sustainable clean energy may be a story of untapped potential, with undue dependence on thermal power. In 2016, Delhi government’s solar policy proposed to install a capacity of 2,000MW from solar generation by 2025. Only a fraction of this has been achieved two years from the deadline. And despite failing to meet its ambitious target, the policy revised the target to 6,000MW by 2025. TimesView At a time when global warming due to the worsening state of the environment is among the most pressing issues of the world, the need to harness solar energy cannot be overemphasized. Solar energy is clean, and indirectly helps in improving the environment. It is, therefore, a matter of concern that Delhi is falling behind its solar energy target. Authorities must ensure that the process is brought to speed. “The Delhi Solar Policy aims to meet 25% of the capital's annual electricity demand through solar energy by 2025, which currently stands at 9%. To achieve this, the policy has set a target of installing solar infrastructure with a capacity of 6,000MW by 2025, which will include 750 MW of rooftop solar,” said finance minister Kailash Gehlot in his budget speech recently. “The policy also aims to generate around 12,000 green jobs in Delhi. The draft policy was shared with the public for their suggestions and comments. Based on their inputs, Delhi government will notify the new policy by April 2023.” According to experts, the state government needs to find alternatives for power generation. “At the current pace Delhi will reach nowhere,” declared Binit Das, deputy programme manager (renewables), Centre for Science and Environment. “The authorities must address several issues, including realising full potential for solar generation. There is absolutely no space on the rooftops of apartments, occupied as they are by water tanks and AC units.” Das pointed out that while the provision of free power units means rooftop solar generation in residential houses does not receive the kind of encouragement it does in other states. “Under the circumstances, the new target seems impractical. We don’t see any major tender being awarded or steps being taken, apart from the draft policy,” noted Das. “The government must do a potential analysis on how much power can be generated from rooftops alone and then call for bids.” Because of the limited space in the city, the state government must think of a solar power plant elsewhere, perhaps in an arrangement with other state governments, and compensate the national grid for the units it consumes in Delhi-NCR. “Delhi Metro is already doing it through its plant in Madhya Pradesh,” Das pointed out. “There are some transmission charges. This wouldn’t be direct power generation, but virtual generation.” The 2016 policy had a provision for mandatory installation for solar panels on all government buildings with rooftops of 500 square metres or above. For other buildings, under the building byelaws, solar panel installation was made mandatory for a plot area measuring 105 sq metres or above. The draft Solar Policy of Delhi 2022 aims at achieving 750MW of rooftop solar power generation by 2025. Given the rooftop capacity of 202MW at present, the state will require accelerated implementation of demand aggregation, such as community solar power to meet this target. Such models will allow all kinds of rooftop owners to participate by pooling investment and sharing the benefits.

• Urban Lab

Delhi has no action plan to soften heatwave blow, yet

The mercury is set to soar this month, but the city currently has no heat action plan for minimising the impact of heatwaves that severely impact Delhiites, especially vulnerable community members.However, a Delhi government official said concerned departments have been asked to submit their plans by April 10. “A draft heat action plan has been prepared. Based on inputs received from departments, a plan will be finalised this month.” The Delhi state action plan on climate change for the current decade is also yet to be implemented. The capital was under the grip of 17 heatwaves last summer, but some locations saw more than 20 heatwave days. delhi heatwave Since the temperature is expected to rise from this month, experts emphasised that a heat action plan should be in place. Aditya Valiathan Pillai, associate fellow at Centre for Policy Research (CPR), said, “Delhi should issue a heat action plan as the city has a large heat-exposed population and dense urban environments that trap heat, particularly in unplanned neighbourhoods, every summer. This summer is predicted to be bad, and it won’t be the last.” He added, “The economic and health consequences of a heatwave that lasts a week or so with hot nights that prevent the body from recovering and a marginal increase in humidity could be devastating. Outdoor workers, including construction workers, traffic police, vendors and delivery agents, are among the vulnerable constantly exposed to heat and have the least flexibility to cope.” Pillai co-authored a CPR report, titled ‘How is India adapting to heatwaves?’ The report stated that heat action plans regularly include a heatwave warning system, including sharing alerts with vulnerable populations; means of coordination between government departments; an awareness, training and behaviour change component to reduce heat exposure; a list of short-term actions, focused on healthcare or changing work hours; and longer-term solutions, such as investing in infrastructure like cool roofs and water harvesting bodies, changes in agricultural practice or adjusting urban planning, including green corridors. Avikal Somvanshi, senior programme manager, urban lab, Centre for Science and Environment, said, “Unlike Ahmedabad and other cities, Delhi has no defined policy for dealing with heatwaves. Heatwaves have become even more problematic in cities due to urban heat islands. When the ambient temperature is 46-50 degrees Celsius, the surface temperature is about 64-65 degrees Celsius, which is highly dangerous for human health.” “When temperature crosses a certain limit, there should be a policy on providing cool and shaded spaces to workers and changing the outdoor working timings,” he added. Meanwhile, IMD plans to issue a heat-hazard analysis for the country, including Delhi, this summer. The department currently issues forecasts based on the maximum temperature and its departure from normal. The heat-hazard analysis will be calculated based on five meteorological factors -- relative humidity, minimum and maximum temperatures, wind speed and duration of heatwave spell.

• Clean Air & Sustainable Mobility

Nearly 50% of Total Sanctioned Posts Vacant in State Pollution Control Boards

Despite pollution becoming a dire concern, nearly 50% of the total sanctioned posts are lying vacant in various state pollution control boards, the government informed Lok Sabha on Monday. According to the data, out of the total 11,103 posts, as many as 5,454 remain vacant. Tasked with implementation of environmental laws across the country, the state pollution control Boards (SPCBs) have a very important role in enforcement of provisions of Water (Prevention and Control of Pollution) Act, 1974, Air (Prevention and Control of Pollution) Act, 1981 and the Environment (Protection) Act, 1986. “Availability of adequate manpower in these institutions is very important for effective discharge of their functions and duties. The responsibility to fill up vacancies in SPCBs/PCCs lies with the concerned State Govt./UT Administration,” Minister of State in the Ministry of Environment, Forest and Climate Change (MoEFCC) Ashwini Kumar Choubey told Parliament. While Bihar has only been able to fill 58 of the total 264 provisioned posts, Jharkhand has filled up only 34 posts out of the total 271 in the state. The vacancy is as high as 64% in Madhya Pradesh, and over 40% in big states like Uttar Pradesh, Rajasthan and West Bengal. Burdened with the highest level of air pollution among all cities, Delhi alone has 192 posts vacant out of total 344 sanctioned posts in the Pollution Control Committee (PCC). Among the northern states, Punjab and Haryana, that struggle to cope with the annual challenge of stubble burning, have as many as 298 and 384 posts vacant, respectively. “It is a dismal picture, especially in some of these states where a lot of work has to be done. The monitoring of water quality at multiple points, as well tracking industrial effluents primarily lies with the state boards. There is a lot of data that needs to be collected and updated,” a former pollution control board official told News18. While the states often cite fund crunch as a problem, the manpower shortage has impeded action on the ground, say experts. Tasked with the implementation of various environmental/pollution control laws, the boards are required to monitor and take steps to abate the rising pollution levels. The responsibility of prevention of pollution of water sources by industrial effluents primarily lies with the states. A recent analysis from the Delhi-based Centre for Science and Environment (CSE) showed how smaller towns smaller and upcoming cities are becoming pollution hotspots and require urgent and deliberate action. The minister also informed Parliament that the Central Pollution Control Board (CPCB) has at least 193 posts vacant against the sanctioned posts of 577. “CPCB has published advertisement for filling of various vacant posts through direct recruitment in Employment News dated December 24-30, 2022,” he added. Nagaland and Arunachal Pradesh emerge as the only states with zero vacancy, followed by Sikkim, Tripura, Mizoram and Goa with just a few posts vacant in otherwise smaller departments, as per the data shared by the government.

• Urban Lab

Smaller towns in eastern states record higher pollution this winter – says CSE’s latest analysis

Cities in India’s eastern states are increasingly falling into the pincer grip of toxic particulate pollution during winter season – and the problem is spreading quickly to the smaller cities and towns of the region: says a latest assessment by Centre for Science and Environment (CSE) released here today. The assessment also notes that though the bigger cities in the region – like Patna and Kolkata — that are part of the National Clean Air Programme (NCAP), have witnessed a marginal improvement in the winter average of their PM2.5 levels compared to the previous two winters, their levels are still high. The smaller towns of Bihar — Begusarai, Bettiah and Siwan in particular — have recorded the worst winter air in the region, with their seasonal average exceeding 200 microgram per cubic metre (µg/m³). Nitrogen dioxide (NO2) pollution is also high in the cities and towns of the region, with Arrah in Bihar recording a staggering 113 µg/m³ monthly average for November, notes CSE. “This analysis is a stark reminder of the rapid spread of pollution. More cities and smaller towns are scaling the pollution height and dotting the pollution map. This once again vindicates the need for a strong state-wide and regional management of air pollution. This is needed to control local pollution sources including vehicles, industry, open burning and construction dust, as well as the impact of upwind pollution sources on downwind cities and towns,” says Anumita Roychowhdury, executive director, research and advocacy, CSE. “Additionally, data gap is also a challenge in the region. Even though the real time monitors have increased in the region including in Jharkhand, some of these could not be used due to data gaps and quality issues. Some of these are new and therefore long term data is not available. The data, thus, is indicative of the current status and seasonal variation in particulate pollution in medium and smaller cities,” says Avikal Somvanshi, senior programme manager, Urban Lab, CSE. With the winter season coming to an end, the Urban Lab at CSE has analysed air quality trends during the winter months (October 2022 to February 2023) in cities of the eastern states of West Bengal, Bihar and Odisha. This is an assessment of seasonal trends in PM2.5 concentration for the period October 1, 2022 to February 28, 2023 for 2019, 2020, 2021, 2022 and 2023. Winter inversion and cool and calm conditions trap local pollution that is already high. This is part of the third edition of the Urban Lab’s Air Quality Tracker Initiative since 2020-21. This analysis covers 50 continuous ambient air quality monitoring stations (CAAQMS) spread across 32 cities in the three states: West Bengal: seven stations in Kolkata, three in Howrah, and one each in Asansol, Siliguri, Durgapur and Haldia. Real time monitors in Durgapur and Haldia became operational only by the end of 2020. Bihar: Six stations in Patna, three each in Gaya and Muzaffarpur, two in Bhagalpur, and one each in Hajipur, Bettiah, Bihar Sharif, Darbhanga, Motihari, Araria, Arrah, Chhapra, Katihar, Kishanganj, Manguraha, Munger, Purnia, Rajgir, Saharsa, Sasaram, Siwan, Aurangabad, Begusarai and Samastipur Odisha: One real time station each in Talcher and Brajrajnagar. Many new stations have been added in November 2022 — one station each in Baripada, Bileipada, Keonjhar, Nayagarh, Rairangpur, Rourkela, Suakati and Tensa. Only a limited long term trend analysis has been possible for the cities that have added stations and monitors relatively recently (like some of the cities in Odisha). Jharkhand has no working monitoring stations, and hence, offers no PM2.5 data for the last two years – which is why its cities have not been included in this analysis. This analysis is based on the real time data available from the current working air quality monitoring stations in east India. Somvanshi says a huge volume of data points have been cleaned and data gaps addressed based on the United States Environmental Protection Agency (USEPA) method for this analysis. Key findings of the CSE analysis Eastern states have experienced the most polluted winter season since 2019-20: The average PM2.5 level across nine cities of east India with functional CAAQMS stations since 2019 stood at 97 µg/m³ this winter. The PM2.5 level was 6 per cent higher compared to the average of previous three winters. The daily peak of the season was recorded on January 1, 2023 and the daily regional average stood at 173 µg/m³. The peak was 24 per cent higher compared to the peak of 2021-22 winter and 8 per cent higher compared to the mean peak of previous three winters. Most cities have experienced worsening of winter PM2.5 levels: West Bengal’s winter average PM2.5 this year is 14 per cent higher than that in the previous winter. Bihar registered a 26 per cent rise, and Odisha a 44 per cent higher winter average compared to the previous winter. On a long term basis, Bihar registered an 18 per cent increase and Odisha a 4 per cent increase from the mean level of previous three winters. However, the seasonal air quality in West Bengal this winter is 4 per cent better than the mean of previous three winters. In absolute concentration terms, Bihar with an average PM2.5 level of 134 µg/m³ was the most polluted state in the east, followed by West Bengal with average PM2.5 level of 84 µg/m³; Odisha was third with a seasonal average of 63 µg/m³. Peak pollution is dangerously high in all eastern states: In absolute concentration terms, Bihar’s daily peak PM2.5 level of 287 µg/m³ was the highest among the three states. West Bengal’s peak was 152 µg/m³ and Odisha’s, 112 µg/m³. In the long term, the seasonal peak in West Bengal this winter has been 1 per cent better than the mean of previous three winter peaks. Bihar registered a 26 per cent increase and Odisha a 14 per cent increase in their peaks compared to the mean of previous three winter peaks. Smaller cities of Bihar are most polluted in the region: Begusarai was the most polluted city in the east with an average PM2.5 level of 275 µg/m³. It was followed by Siwan with 203 µg/m³, Bettiah (202 µg/m³), Katihar (188 µg/m³), and Saharsa (180 µg/m³). All the top 20 most polluted cities of the east are located in Bihar. In West Bengal, Asansol, with a winter average of 102 µg/m³ was the most polluted city; it is followed by Howrah (92 µg/m³) at the second spot. Talcher (75 µg/m³) was the most polluted in Odisha – however, adds Somvanshi, “since only two cities in the state have real time monitors with adequate data for assessment, it is not possible to capture the larger landscape.” Haldia in West Bengal was the least polluted city among the three states with a PM2.5 average of 46 µg/m³, followed by Siliguri in West Bengal and Manguraha in Bihar with winter averages of 60 µg/m³ and 66 µg/m³, respectively. Patna registered the highest increase in winter pollution this winter among the major cities in the region: Patna in Bihar and Talcher in Odisha were the worst performers and registered an increase of 39 per cent and 41 per cent from the previous year, respectively. These were followed by Asansol in West Bengal and Gaya in Bihar, which recorded an increase of 38 per cent and 37 per cent, respectively. Howrah (0 per cent), Kolkata (3 per cent) and Muzaffarpur (8 per cent) registered nil to marginal increases in pollution levels this season compared to the previous winter. Haldia and Durgapur are the only two cities that have shown improvement in air quality this season compared to the corresponding period in the previous year. Durgapur registered the maximum improvement — 30 per cent lower PM2.5 levels compared to the previous year; Haldia clocked a 19 per cent dip. Increasing levels of NO2 in November: There was a significant increase in NO2 concentrations during November compared to the months of October and September. NO2 comes entirely from combustion sources and significantly, from vehicles. Patna registered the greatest increase — 2.9 times — with the maximum build-up of NO2 between September and November 2022. Katihar and Rajgir each registered a 2.6 times increase in NO2. Motihari, Kolkata and Howrah registered a 2.3 times hike. In absolute concentration terms, Arrah in Bihar registered the highest NO2 average of 113 µg/m³ (see Graph in the detailed report). It is followed by Bhagalpur with 98 µg/m³ and Siwan with 89 µg/m³. Among West Bengal cities, Asansol with a monthly average of 40 µg/m³ was the most polluted. Diwali pollution was the highest in the small towns of Bihar among the eastern states: The Diwali of this winter was less polluted compared to the previous year’s Diwali for all the major cities in the region. However, the smaller cities of Bihar witnessed the maximum increase in pollution levels on Diwali night. In fact, pollution level on Diwali night (8 pm to 8 am) shot up by 0.2-2.3 times the average level recorded during the seven nights preceding Diwali. Nine out of 32 stations recorded an increase in pollution on the day of Diwali. Motihari in Bihar saw the greatest jump of 2.3-times higher PM2.5 level — 152 µg/m³ — on Diwali night. It was followed by Siwan and Bettiah each with 1.8-times higher PM2.5 concentrations. Bihar cities dominate the top 15 list of cities with the most polluted Diwali nights. Among West Bengal cities, Asansol recorded a Diwali night PM2.5 level of 42 µg/m³. Haldia and Manguraha each with 12 µg/m³ had the least polluted Diwali night in the region, followed by Durgapur with 13 µg/m³. Step up the action Says Roychowdhury: “High winter pollution is an indicator of a deeper and rapid spread of air pollution in the eastern region. As the winter turns hostile due to inversion and cold and calm conditions, pollution gets trapped and spirals. This requires an aggressive strategy to control pollution not only in the bigger cities, but also across the region to mitigate pollution from vehicles and transportation, industries, open burning of waste, landfill fires, construction, household use of solid fuels, and other area sources. It is necessary to reduce pollution in a targeted manner to meet the clean air standards.”