Impact of crop residue burning in Haryana on the air quality of Delhi, India

Aerosol-PM2.5 Dynamics: In-situ and satellite observations under the influence of regional crop residue burning in post-monsoon over Delhi-NCR, India

The increasing air pollution in the urban atmosphere is adversely impacts the environment, climate and human health. The alarming degradation of air quality, atmospheric conditions, economy and human life due to air pollution needs significant in-depth studies to ascertain causes, contributions and impacts for developing and implementing an effective policy to combat these issues. This work lies in its multifaceted approach towards comprehensive understanding and mitigating severe pollution episodes in Delhi and its surrounding areas. We investigated the aerosol dynamics in the post-monsoon season (PMS) from 2019 to 2022 under the influence of both crop residue burning and meteorological conditions. The study involves a broad spectrum of factors, including PM2.5 concentrations, active fire events, and meteorological parameters, shedding light on previously unexplored studies. The average AOD550 (0.79) and PM2.5 concentration (140.12 μg/m³) were the highest in 2019. PM2.5 was higher from mid-October to mid-November each year, exceeding the WHO guideline of 15 μg/m³ (24 h) by 27-34 times, signifying a public health emergency. A moderate to strong correlation between PM2.5 and AOD was found (r = 0.65) in 2021. The hotspot region accounts for almost 50% (2019), 47.51% (2020), 57.91% (2021) and 36.61% (2022) of the total fire events. A statistically significant negative non-linear correlation (r) was observed between wind speed (WS) and both AOD and PM2.5 concentration, influencing air quality over the region. HYSPLIT model and Windrose result show the movement of air masses predominated from the North and North-West direction during PMS. This study suggest to promotes strategies such as alternative waste management, encouraging modern agricultural practices in hot-spot regions, and enforcing strict emission norms for industries and vehicles to reducing air pollution and its detrimental effects on public health in the region and also highlights the need for future possibilities of research to attract the global attention.

Human health impacts attributable to inhalation exposure of particulate matter (PM10 and PM2.5) during the Holi festival

OBJECTIVE

The present study focuses on residential areas of Delhi to identify the elevated levels of ambient PM10 and PM2.5 due to biomass burning followed by the coloring activity in the Holi festival celebrated at the end of the winter season. This study also focuses on the health risk assessment and mortality among different age groups due to the change in particulate matter levels during the Holi festival in Delhi, India.

MATERIALS AND METHODS

Secondary data of particulate matters have been procured from the Central Pollution Control Board (CPCB), Delhi Pollution Control Committee (DPCC), and Indian Institute of Tropical Meteorology (IITM), Pune for the period of the pre-, during, and post-Holi period for the year 2018-2020 at four selected residential locations in Delhi, India. The health impacts of particle inhalation were quantified using the AirQ + models.

RESULTS

The results indicated the levels of PM10 and PM2.5 rise about 3-4 times higher during the Holi festival than on normal days, resulting in health risks and causing an excess number of mortality and Asthma cases in Delhi. Such cases were also found to be higher in 2018, followed by 2019 and 2020 at all the selected locations in Delhi.

CONCLUSIONS

The study linked the increasing particulate levels in the Holi festival with the increased health risk through short-term exposure of the population. The excess number of cases (ENCs) of mortality, all causes of mortality among adults (age > 30 years) associated with short-term exposure to particulate were also identified.

Quantifying the impact of lockdown measures on air pollution levels: A comparative study of Bhopal and Adelaide

This research study presents an in-depth comparison of air quality in Bhopal, India, and Adelaide, Australia, focusing on the impact of COVID-19 restrictions. Utilizing air quality data from 2019 to 2022, the research analyzed the concentrations of pollutants like PM2.5, PM10, NO2, and O3, during pre-lockdown, lockdown, and post-lockdown periods. The findings demonstrate a significant reduction in PM2.5and PM10 levels during lockdown in cities such as Delhi and Haryana in India, and various Chinese cities, while also highlighting complex sources of air pollution like bushfires in regions like Sydney, Australia. In contrast, the study revealed nuanced trends in Bhopal and Adelaide, influenced by local geographical, climatic, and anthropogenic factors. Bhopal exhibited a notable decrease in PM10 and PM2.5levels, but inconsistent patterns in NO2 and CO, while Adelaide experienced marginal changes. The study emphasizes the temporary effectiveness of lockdowns and underscores the need for region-specific, sustainable air quality management strategies. Future implications include considerations for regional specificities, broader atmospheric chemistry, and international collaboration. The research provides valuable insights for urban air quality policy formulation, stressing a data-driven, long-term approach.

Seasonal correlation of aerosols with soil moisture, evapotranspiration, and vegetation over Pakistan using remote sensing

Aerosols have a severe impact on the Earth's climate, human health, and ecosystem. To understand the impacts of aerosols on climate, human health, and the ecosystem we must need to understand the variability of aerosols and their optical properties. Therefore, we used Aqua-MODIS retrieved aerosol optical depth (AOD) (550 nm) and Angstrom exponent (AE) (440/870) data to analyze the Spatio-temporal seasonal variability of aerosols and their relationship with different meteorological parameters over Pakistan from 2002 to 2021. High (>0.5) AOD values were observed during the summer season and low (<0.8) in the spring season. AE values were observed to be high (>1) in the northern regions of Pakistan indicating the dominance of fine mode particles during the winter season. Moreover, AOD showed a positive correlation with Relative Humidity (RH), Evapotranspiration, Wind speed (WS), and Temperature. On the other hand, it showed a negative correlation with Soil moisture (SM), Normalized difference vegetation index (NDVI), and precipitation over Pakistan. Therefore, considering the outcomes of this study will help policymakers to understand the spatiotemporal variability of aerosols and their seasonal correlation with different meteorological parameters.

Contribution of low birth weight to childhood undernutrition in India: evidence from the national family health survey 2019-2021

BACKGROUND

Infants born with low birth weight (LBW), i.e. less than 2500g, is considered an important factor of malnutrition in Asia. In India, research related to this issue is still neglected and limited. Evidence exists that a large number of child deaths occur in India due to maternal and child malnutrition-related complications. Moreover, it has been found that the cost of malnutrition in India results in a significant reduction of the country's Gross Domestic Product (GDP). Thus, in this current context, this study aims to explore the contribution of low birth weight to childhood undernutrition in India.

METHODS

The study used data from the 5^th round of the National Family Health Survey (NFHS-5), a large-scale survey conducted in India. The survey collected information from 176,843 mothers and 232,920 children. The study used the last birth information (last children born 5 years preceding the survey) due to the detailed availability of maternal care information. Univariate and bivariate analyses were conducted to determine the percentage distribution of outcome variables. Multivariate logistic regression was employed to examine the association between LBW and undernutrition (stunting, wasting, and underweight). The study also used the Fairlie decomposition analysis to estimate the contribution of LBW to undernutrition among Indian children.

RESULTS

The results show that childhood undernutrition was higher in states like Uttar Pradesh, Bihar, Jharkhand, Gujarat, and Maharashtra. The results of the logistic regression analysis show that infants born with low birth weight were more likely to be stunted (OR = 1.46; 95% CI: 1.41-1.50), wasted (OR = 1.33; 95% CI: 1.27-1.37), and underweight (OR = 1.76; 95% CI: 1.70-1.82) in their childhood compared to infants born without low birth weight. The findings from the decomposition analysis explained that approximately 14.8% of the difference in stunting, 10.4% in wasting, and 9.6% in underweight among children born with low birth weight after controlling for the individuals' selected characteristics.

CONCLUSION

The findings suggest that LBW has a significant contribution to malnutrition. The study suggests that policymakers should prioritize strengthening maternal and child healthcare schemes, particularly focusing on antenatal and postnatal care, as well as kangaroo mother care at the grassroots level to reduce the burden of LBW and undernourished children.

Stubble-burning activities in north-western India in 2021: Contribution to air pollution in Delhi

Stubble-burning in northern India is an important source of atmospheric particulate matter (PM) and trace gases, which significantly impact local and regional climate, in addition to causing severe health risks. Scientific research on assessing the impact of these burnings on the air quality over Delhi is still relatively sparse. The present study analyzes the satellite-retrieved stubble-burning activities in the year 2021, using the MODIS active fire count data for Punjab and Haryana, and assesses the contribution of CO and PM_2.5 from such biomass-burning activities to the pollution load in Delhi. The analysis suggests that the satellite-retrieved fire counts in Punjab and Haryana were the highest among the last five years (2016-2021). Further, we note that the stubble-burning fires in the year 2021 are delayed by ∼1 week compared to that in the year 2016. To quantify the contribution of the fires to the air pollution in Delhi, we use tagged tracers for CO and PM_2.5 emissions from fire emissions in the regional air quality forecasting system. The modeling framework suggests a maximum daily mean contribution of the stubble-burning fires to the air pollution in Delhi in the months of October-November 2021 to be around 30-35%. We find that the contribution from stubble burning activities to the air quality in Delhi is maximum (minimum) during the turbulent hours of late morning to afternoon (calmer hours of evening to early morning). The quantification of this contribution is critical from the crop-residue and air-quality management perspective for policymakers in the source and the receptors regions, respectively.

Climatology and landscape determinants of AOD, SO2 and NO2 over Indo-Gangetic Plain

Indo-Gangetic Plains (IGP) experiences high loading of particulate and gaseous pollutants all year around and is considered to be the most polluted regions of India. Understanding the effect of landscape determinants on air pollution in IGP regions is crucial to make its environment sustainable. We examined satellite retrievals of OMI NO₂ and SO₂, and MODIS AOD to analyse the long-term trend, spatio-seasonal pattern and dynamics of aerosols, NO₂ and SO₂ over three IGP regions, namely Upper Indo-Gangetic plain (UIGP), Middle Indo-Gangetic plain (MIGP) and Lower Indo-Gangetic plain (LIGP) over the period 2005-2019. IGP experienced an overall increment in AOD (R² = 0.63) and SO₂ (R² = 0.67) values, with LIGP (AOD, R² = 0.8 & SO₂, R² = 0.8) experiencing the largest rate of enhancement. The levels of NO₂ (R² = 0.2) experienced a decrement after 2012 (owing to implementation of vehicle emission policy) except in MIGP, with UIGP (R² = 0.23) exhibiting the largest rate of decrement. Seasonal heterogeneity in the nature of sources was observed over IGP regions. AOD (0.61 ± 0.1) and NO₂ value (3.82 ± 0.98 × 10¹⁵ molecules/cm²) were found highest during post-monsoon in UIGP owing to crop residue burning activity. The value of NO₂ (3.8 ± 1.4 × 10¹⁵ molecules/cm²) in MIGP was found highest during pre-monsoon due to high consumption of coal in power plants for summer cooling demand. The highest SO₂ level (0.09 ± 0.06 DU) was observed during post-monsoon in UIGP, as a large number of brick kilns are fired during this period. Correlations among landscape determinants and pollutants revealed that topography is the dominant variable that affect the spatial pattern of AOD compared to vegetation and land use. Lower elevation tends to have high AOD values compared to higher elevation. Vegetation-AOD relationship showed an inverse association in IGP regions and is influenced by factors such as seasonal meteorology and size of the airborne particles. Vegetation possesses positive relationship with SO₂ and NO₂, implying no pollution abatement effect on SO₂ and NO₂ pollutants. Built-up change has deteriorating effect as well as quenching effect on pollutants. Increase in built terrain have deteriorated the air quality in UIGP whereas it favored in suppressing the aerosol level in LIGP.

Relationship between low birth weight and infant mortality: evidence from National Family Health Survey 2019-21, India

BACKGROUND

Low birth weight (LBW) predisposes physical and mental growth failure and premature death among infants. Studies report that LBW predominately explains infant mortality. However, existing studies rarely demonstrate the phenomenon of both observed and unobserved factors, which may influence the likelihood of birth and mortality outcomes simultaneously. In this study, we identified the spatial clustering of the prevalence of LBW along with its determinants. Further, the relationship between of LBW and infant mortality, considering the unobserved factors, has been explored in the study.

METHODS

Data for this study have been extracted from the National Family Health Survey (NFHS) round 5, 2019-21. We used the directed acyclic graph model to identify the potential predictors of LBW and infant mortality. Moran's I statistics have been used to identify the high-risk areas of LBW. We applied conditional mixed process modelling in Stata software to account for the simultaneous nature of occurrences of the outcomes. The final model has been performed after imputing the missing data of LBW.

RESULTS

Overall, in India, 53% of the mothers reported their babies' birth weight by seeing health card, 36% reported by recall, and about 10% of the LBW information was observed as missing. The state/union territory of Punjab and Delhi were observed to have the highest levels of LBW (about 22%) which is much higher than the national level (18%). The effect of LBW was more than four times larger compared to the effect in the analysis which does not account for the simultaneous occurrence of LBW and infant mortality (marginal effect; from 12 to 53%). Also, in a separate analysis, the imputation technique has been used to address the missing data. Covariates' effects showed that female children, higher order births, births that occur in Muslim and non-poor families and literate mothers were negatively associated with infant mortality. However, a significant difference was observed in the impact of LBW before and after imputing the missing values.

CONCLUSIONS

The current findings showed the significant association of LBW with infant deaths, highlighting the importance of prioritising policies that help improve the birth weight of new-born children that may significantly reduce the infant mortality in India.

The relationship between PM10 and meteorological variables in the mega city Istanbul

PM₁₀, one of the air pollutants, occurs regularly in İstanbul during the winter months, namely in December, January, and February. PM₁₀ pollutant is affected by numerous factors. Among these factors are various meteorological variables and climatological factors. This article aims to determine the relationship between PM₁₀ and meteorological variables (wind speed, wind direction, temperature, and relative humidity) and to interpret these results. PM₁₀ and meteorological data were examined between 2011 and 2018. To determine the relationship, multiple linear regression, Pearson's correlation coefficient (PCC), Spearman's rank correlation, Kendall Tau correlation, autocorrelation function (ACF), cross-correlation function (CCF), and visuals were determined using the R program (open-air) packages. In the study, the relationship between wind, temperature, and relative humidity with PM₁₀ was determined, and it was observed that the PM₁₀ concentration was maximum between January and February. PM₁₀ concentrations have a positive relationship with relative humidity and wind direction, while a negative relationship with wind speed and temperature was observed. The correlation values for relative humidity and temperature were found to be 0.01 and - 0.15, respectively. Furthermore, the relationship between wind speed and PM₁₀ was calculated from multiple linear regression model, and the estimated value was - 0.12 while looking at the wind direction value, it was approximately 0.03.

Profile of atmospheric particulate PAHs near busy roadway in tropical megacity, India

Objective: This study focuses on the profile of ambient particulate polycyclic aromatic hydrocarbons (PAHs), their seasonal distribution, source identification and human health risk assessment due to inhalation exposure of ambient PAHs in Delhi, India.Materials and Methods: Two sampling sites were chosen, one at roadway (MH) and other at urban background (JNU) site in Delhi. Determination of PAHs was carried with the help of HPLC with UV detector. Principal component analysis and Molecular diagnostic ratios were used for the source apportionment of PAHs. Health risks associated with inhalation of particulate PAHs were assessed using benzo(a)pyrene equivalent concentration and incremental lifetime cancer risk (ILCR) approach.Results: The results showed that the average mass concentration of Σ₁₆ PAHs near roadway (67.8 ± 40.2 ng m^-3) is significantly higher than urban background site (56 ± 30 ng m^-3). Moreover, source apportionment study indicated that major PAH-emission sources in Delhi NCR are traffic and coal combustion. ILCR values at both the sites fall in the range of 10^-2-10^-4 that corresponds to the priority risk level (10^-3) and higher than the acceptable risk level (10^-6).conclusions: The high PAHs concentration at MH site was due to it's nearness to busy traffic area. Thus, the spatial variations in PAHs were influenced by local emission sources. The high PAHs level during the winter season can be due to their higher emissions from local heating sources, shift of gas/particle partitioning toward the particulate phase at low temperature and reduced photochemical degradation of some PAHs in winter. The low level of PAHs in monsoon season can be attributed to their wet scavenging and higher percentage in vapor phase. PCA showed that the emissions from vehicles predominate at MH site; whereas, coal combustion and traffic both are the significant PAHs sources at JNU site. Health risk assessment revealed that the highest exposure risks occur at busy traffic site, thereby indicating a significantly higher health risk to the population of Delhi.

Can Forest Fires Be an Important Factor in the Reduction in Solar Power Production in India?

The wildfires over the central Indian Himalayan region have attracted the significant attention of environmental scientists. Despite their major and disastrous effects on the environment and air quality, studies on the forest fires’ impacts from a renewable energy point of view are lacking for this region. Therefore, for the first time, we examine the impact of massive forest fires on the reduction in solar energy production over the Indian subcontinent via remote sensing techniques. For this purpose, we used data from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIPSO), the Satellite Application Facility on support to Nowcasting/Very Short-Range Forecasting Meteosat Second Generation (SAFNWC/MSG) in conjunction with radiative transfer model (RTM) simulation, in addition to 1-day aerosol forecasts from the Copernicus Atmosphere Monitoring Service (CAMS). The energy production during the first quarter of 2021 was found to reach 650 kWh/m2 and the revenue generated was about INR (Indian rupee) 79.5 million. During the study period, the total attenuation due to aerosols and clouds was estimated to be 116 and 63 kWh/m2 for global and beam horizontal irradiance (GHI and BHI), respectively. The financial loss due to the presence of aerosols was found to be INR 8 million, with the corresponding loss due to clouds reaching INR 14 million for the total Indian solar plant’s capacity potential (40 GW). This analysis of daily energy and financial losses can help the grid operators in planning and scheduling power generation and supply during the period of fires. The findings of the present study will drastically increase the awareness among the decision makers in India about the indirect effects of forest fires on renewable energy production, and help promote the reduction in carbon emissions and greenhouse gases in the air, along with the increase in mitigation processes and policies.

Investigation of Forest Fire Activity Changes Over the Central India Domain Using Satellite Observations During 2001-2020

Recurrent and large forest fires negatively impact ecosystem, air quality, and human health. Moderate Resolution Imaging Spectroradiometer fire product is used to identify forest fires over central India domain, an extremely fire prone region. The study finds that from 2001 to 2020, ∼70% of yearly forest fires over the region occurred during March (1,857.5 counts/month) and April (922.8 counts/month). Some years such as 2009, 2012, and 2017 show anomalously high forest fires. The role of persistent warmer temperatures and multiple climate extremes in increasing forest fire activity over central India is comprehensively investigated. Warmer period from 2006 to 2020 showed doubling and tripling of forest fire activity during forest fire (February-June; FMAMJ) and non-fire (July-January; JASONDJ) seasons, respectively. From 2015 JASONDJ to 2018 FMAMJ, central India experienced a severe heatwave, a rare drought and an extremely strong El Niño, the combined effect of which is linked to increased forest fires. Further, the study assesses quinquennial spatiotemporal changes in forest fire characteristics such as fire count density and average fire intensity. Deciduous forests of Jagdalpur-Gadchiroli Range and Indravati National Park in Chhattisgarh state are particularly fire prone (>61 fire counts/grid) during FMAMJ and many forest fires are of high intensity (>45 MW). Statistical associations link high near surface air temperature and low precipitation during FMAMJ to significantly high soil temperature, low soil moisture content, low evapotranspiration and low normalized difference vegetation index. This creates a significantly drier environment, conducive for high forest fire activity in the region.