Explore the vast range of titles available.

Air pollution is the most difficult challenge India is facing today, and anthropogenic biomass burning (ABB) is one of the major and least understood sources, leading to serious health and climate implications by affecting air quality, visibility, atmospheric chemistry, the Earth’s radiation budget and biogeochemical cycling. Scientific understanding of the composition, chemistry and regional dynamics of biomass burning (BB) emissions is still limited, thus constraining the implementation of appropriate research and policy interventions. The broad categories, associated complex emissions and spatio-temporal variations of ABB in India are discussed here. Major types of ABB that are prevalent year-round all over India include BB for cooking, heating purposes and open waste burning. Moreover, crop residue burning (CRB) in the Indo-Gangetic plain (IGP) during pre- (April–May) and post-monsoon (October–November) seasons, CRB in South India during January–February, forest fires in Central India and slash-and-burn agriculture in Northeast India during March–May are the other dominant sources that are active during specific months and in specific regions. Over the IGP, CRB along with other episodic ABB events and stagnant meteorology result in severe air quality and poor visibility (<∼300 m) with reported daily mean PM 2.5 concentrations shooting up to 15 times higher than Central Pollution Control Board standards. When compared with wheat residue burning, higher fire counts and emissions are reported during paddy residue burning events. During winters, BB’s contribution to 37% of the aerosol oxidative potential in Delhi indicates its health implications. Meta-analysis of data obtained from representative source apportionment studies on PM 10 shows >24% BB contribution in Assam, Ahmedabad, Kanpur and Visakhapatnam, 20%–24% in Patiala and Kolkata, and 10%–14% in Delhi. With regard to PM 2.5 , BB contributions of >24% in Ahmedabad and Agra, and 15%–19% in Delhi, Mumbai and Kolkata are reported, while with regard to PM 1 , BB contributed 19%–24% in Kanpur, Patiala and Assam and <10% in Delhi. Observed spatio-temporal variations in ABB sources and composition over India call for region-specific solutions through airshed-based management.

Measurements and models show that enhanced aerosol concentrations can modify macro- and micro-physical properties of clouds. Here, we examine the effect of aerosols on continental mesoscale convective cloud systems during the Indian summer monsoon and find that these aerosol–cloud interactions have a net cooling effect at the surface and the top-of-atmosphere. Long-term (2002–2016) satellite data provide evidence of aerosol-induced cloud invigoration effect (AIvE) during the Indian summer monsoon. The AIvE leads to enhanced formation of thicker stratiform anvil clouds at higher altitudes. These AIvE-induced stratiform anvil clouds are also relatively brighter because of the presence of smaller sized ice particles. As a result, AIvE-induced increase in shortwave cloud radiative forcing is much larger than longwave cloud radiative forcing leading to the intensified net cooling effect of clouds over the Indian summer monsoon region. Such aerosol-induced cooling could subsequently decrease the surface diurnal temperature range and have significant feedbacks on lower tropospheric turbulence in a warmer and polluted future scenario. The invigoration of deep convective clouds in the Indian summer monsoon region is associated with high aerosol loading. Here the authors show that convective clouds from high aerosol loads in the Indian Summer Monsoon region have a cooling effect.

Low-cost particulate matter (PM) sensors are promising tools for supplementing existing air quality monitoring networks. However, the performance of the new generation of low-cost PM sensors under field conditions is not well understood. In this study, we characterized the performance capabilities of a new low-cost PM sensor model (Plantower model PMS3003) for measuring PM2.5 at 1 min, 1 h, 6 h, 12 h, and 24 h integration times. We tested the PMS3003 sensors in both low-concentration suburban regions (Durham and Research Triangle Park (RTP), NC, US) with 1 h PM2.5 (mean ± SD) of 9±9 and 10±3 µg m−3, respectively, and a high-concentration urban location (Kanpur, India) with 1 h PM2.5 of 36±17 and 116±57 µg m−3 during monsoon and post-monsoon seasons, respectively. In Durham and Kanpur, the sensors were compared to a research-grade instrument (environmental β attenuation monitor, E-BAM) to determine how these sensors perform across a range of PM2.5 concentrations and meteorological factors (e.g., temperature and relative humidity, RH). In RTP, the sensors were compared to three Federal Equivalent Methods (FEMs) including two Teledyne model T640s and a Thermo Scientific model 5030 SHARP to demonstrate the importance of the type of reference monitor selected for sensor calibration. The decrease in 1 h mean errors of the calibrated sensors using univariate linear models from Durham (201 %) to Kanpur monsoon (46 %) and post-monsoon (35 %) seasons showed that PMS3003 performance generally improved as ambient PM2.5 increased. The precision of reference instruments (T640: ±0.5 µg m−3 for 1 h; SHARP: ±2 µg m−3 for 24 h, better than the E-BAM) is critical in evaluating sensor performance, and β-attenuation-based monitors may not be ideal for testing PM sensors at low concentrations, as underscored by (1) the less dramatic error reduction over averaging times in RTP against optically based T640 (from 27 % for 1 h to 9 % for 24 h) than in Durham (from 201 % to 15 %); (2) the lower errors in RTP than the Kanpur post-monsoon season (from 35 % to 11 %); and (3) the higher T640–PMS3003 correlations (R2≥0.63) than SHARP–PMS3003 (R2≥0.25). A major RH influence was found in RTP (1 h RH =64±22 %) due to the relatively high precision of the T640 measurements that can explain up to ∼30 % of the variance in 1 min to 6 h PMS3003 PM2.5 measurements. When proper RH corrections are made by empirical nonlinear equations after using a more precise reference method to calibrate the sensors, our work suggests that the PMS3003 sensors can measure PM2.5 concentrations within ∼10 % of ambient values. We observed that PMS3003 sensors appeared to exhibit a nonlinear response when ambient PM2.5 exceeded ∼125 µg m−3 and found that the quadratic fit is more appropriate than the univariate linear model to capture this nonlinearity and can further reduce errors by up to 11 %. Our results have substantial implications for how variability in ambient PM2.5 concentrations, reference monitor types, and meteorological factors can affect PMS3003 performance characterization.

Aerosols play important roles in modulations of cloud properties and hydrological cycle by decreasing the size of cloud droplets with the increase of aerosols under the condition of fixed liquid water path, which is known as the first aerosol indirect effect or Twomey-effect or microphysical effect. Using high-quality aerosol data from surface observations and statistically decoupling the influence of meteorological factors, we show that highly loaded aerosols can counter this microphysical effect through the radiative effect to result both the decrease and increase of cloud droplet size depending on liquid water path in water clouds. The radiative effect due to increased aerosols reduces the moisture content, but increases the atmospheric stability at higher altitudes, generating conditions favorable for cloud top entrainment and cloud droplet coalescence. Such radiatively driven cloud droplet coalescence process is relatively stronger in thicker clouds to counter relatively weaker microphysical effect, resulting the increase of cloud droplet size with the increase of aerosol loading; and vice-versa in thinner clouds. Overall, the study suggests the prevalence of both negative and positive relationships between cloud droplet size and aerosol loading in highly polluted regions.

Air quality networks in cities can be costly and inconsistent and typically monitor a few pollutants. Space-based instruments provide global coverage spanning more than a decade to determine trends in air quality, augmenting surface networks. Here we target cities in the UK (London and Birmingham) and India (Delhi and Kanpur) and use observations of nitrogen dioxide (NO2) from the Ozone Monitoring Instrument (OMI), ammonia (NH3) from the Infrared Atmospheric Sounding Interferometer (IASI), formaldehyde (HCHO) from OMI as a proxy for non-methane volatile organic compounds (NMVOCs), and aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS) for PM2.5. We assess the skill of these products at reproducing monthly variability in surface concentrations of air pollutants where available. We find temporal consistency between column and surface NO2 in cities in the UK and India (R = 0.5–0.7) and NH3 at two of three rural sites in the UK (R = 0.5–0.7) but not between AOD and surface PM2.5 (R < 0.4). MODIS AOD is consistent with AERONET at sites in the UK and India (R ≥ 0.8) and reproduces a significant decline in surface PM2.5 in London (2.7 % a−1) and Birmingham (3.7 % a−1) since 2009. We derive long-term trends in the four cities for 2005–2018 from OMI and MODIS and for 2008–2018 from IASI. Trends of all pollutants are positive in Delhi, suggesting no air quality improvements there, despite the roll-out of controls on industrial and transport sectors. Kanpur, identified by the WHO as the most polluted city in the world in 2018, experiences a significant and substantial (3.1 % a−1) increase in PM2.5. The decline of NO2, NH3, and PM2.5 in London and Birmingham is likely due in large part to emissions controls on vehicles. Trends are significant only for NO2 and PM2.5. Reactive NMVOCs decline in Birmingham, but the trend is not significant. There is a recent (2012–2018) steep (> 9 % a−1) increase in reactive NMVOCs in London. The cause for this rapid increase is uncertain but may reflect the increased contribution of oxygenated volatile organic compounds (VOCs) from household products, the food and beverage industry, and domestic wood burning, with implications for the formation of ozone in a VOC-limited city.

While high concentrations of pre-existing particles tend to inhibit new particle formation (NPF) in the atmosphere, severely polluted megacities around the world are becoming hot spots for the latter. We measured the particle number-size distributions with a Scanning Mobility Particle Sizer (SMPS) in the urban environment of Kanpur, India, and discovered that particle bursts occurred on 82% of the observation days, indicating that new particles frequently formed from gaseous precursors despite the relatively high concentrations of pre-existing particles. During such events, Aitken-mode particles contributed more than 50% of the total particle mass. Additionally, we used a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) to assess chemical changes in the sub-micron particles during NPF events. Because the HR-ToF-AMS can not detect particles smaller than 40 nm in diameter, however, it was not possible to investigate the chemistry driving the NPF. Our results indicated that oxygenated organic aerosols (OAs) constituted almost 77%—the largest fraction—of the sub-micron particles. The m/z 57 ion (C 4 H 9 + ), a tracer of hydrocarbon-like OA (HOA), displayed significantly enhanced signal intensity during all of the NPF event days. Moreover, the increased proportion of organic ions, m/z 44 (CO 2 + ), on these days suggested the presence of less volatile, highly oxidized OAs (LV-OOAs), revealing that the growth of new particles was mainly due to the condensation of low-volatility organic species. The substantially elevated signal intensity of amines (viz., CHN + , CH 4 N + , C 2 H 4 N + , C 3 H 8 N + , and C 5 H 12 N + ) in the sub-micron aerosols during NPF further demonstrated that these nitrogen-containing organic compounds may have played a critical role in these events. Thus, our findings emphasize the relevance of amines to secondary aerosol formation in severely polluted urban environments.

The Taj Mahal-an iconic World Heritage monument built of white marble-has become discolored with time, due, in part, to high levels of particulate matter (PM) soiling its surface (Bergin et al 2015 Environ. Sci. Technol. 49 808-812). Such discoloration has required extensive and costly treatment (2015 Two Hundred Sixty Second Report on Effects of Pollution on Taj Parliament of India Rajya Sabha, New Delhi) and despite previous interventions to reduce pollution in its vicinity, the haze and darkening persists (Bergin et al 2015 Environ. Sci. Technol. 49 808-812; 2015 Two Hundred Sixty Second Report on Effects of Pollution on Taj Parliament of India Rajya Sabha, New Delhi). PM responsible for the soiling has been attributed to a variety of sources including industrial emissions, vehicular exhaust and biomass burning, but the contribution of the emissions from the burning of open municipal solid waste (MSW) may also play an important role. A recent source apportionment study of fine particulate matter (PM2.5) at the Taj Mahal showed biomass burning emissions, which would include MSW emissions, accounted for nearly 40% of organic matter (OM)-a component of PM-deposition to its surface (Bergin et al 2015 Environ. Sci. Technol. 49 808-812); dung cake burning, used extensively for cooking in the region, was the suggested culprit and banned within the city limits (2015 Two Hundred Sixty Second Report on Effects of Pollution on Taj Parliament of India Rajya Sabha, New Delhi), although the burning of MSW, a ubiquitous practice in the area (Nagpure et al 2015 Environ. Sci. Technol. 49 12904-12), may play a more important role in local air quality. Using spatially detailed emission estimates and air quality modeling, we find that open MSW burning leads to about 150 ( 130) mg m−2 yr−1 of PM2.5 being deposited to the surface of the Taj Mahal compared to about 12 ( 3.2) mg m−2 yr−1 from dung cake burning. Those two sources, combined, also lead to an estimated 713 (377-1050) premature mortalities in Agra each year, dominated by waste burning in socioeconomically lower status neighborhoods. An effective MSW management strategy would reduce soiling of the Taj Mahal, improve human health, and have additional aesthetic benefits.

Lucknow is the capital of India's largest state, Uttar Pradesh, one of South Asia's most polluted urban cities. Tropospheric photochemistry relies on non-methane volatile organic compounds (NMVOCs), which are ozone and secondary organic aerosol precursors. Using the proton-transfer reaction time-of-flight mass spectrometer (PTR-ToF-MS) at an urban background site in Lucknow, the chemical characterisation of NMVOCs was performed in real time from December 2020 to May 2021. About ∼ 173 NMVOCs from m/z 31.018 to 197.216 were measured during the study period, including aromatics, non-aromatics, oxygenates, and nitrogen-containing compounds. The campaign daily mean concentrations of the NMVOCs were 125.5 ± 37.5 ppbv. The NMVOC daily average concentrations were about ∼ 30 % higher during the winter months (December–February) than in summer (March–May). The oxygenated volatile organic compounds and aromatics were the dominant VOC families, accounting for ∼ 57 %–80 % of the total NMVOC concentrations. Acetaldehyde, acetone, and acetic acid were the major NMVOC species, 5–15 times higher than the other species. An advanced multi-linear engine (ME-2) model was used to perform the NMVOC source apportionment using positive matrix factorisation (PMF). It resolves the five main sources contributing to these organic compounds in the atmosphere. They include traffic (23.5 %), two solid fuel combustion factors, SFC 1 (28.1 %) and SFC 2 (13.2 %), secondary volatile organic compounds (SVOCs) (18.6 %), and volatile chemical products (VCPs) (16.6 %). Aged and fresh emissions from solid fuel combustion (SFCs 1 and 2) were the dominant contributors to the total NMVOCs, and compounds related to these factors had a high secondary organic aerosol (SOA) formation potential. Interestingly, the traffic factor was the second-highest contributor to the total NMVOCs, and compounds related to this factor had a high ozone formation potential. Significant differences in the composition of the two solid fuel combustions indicate the influence of local emissions and transport of regional pollution to the city. The high temperature during summer leads to more volatilisation of oxygenated VOCs, related to the VCP factor. The study is the first attempt to highlight the sources of NMVOCs and their contribution to secondary pollutant (SOA and O3) formation in the city of Lucknow during winter and summer. The insights from the study would help various stakeholders to manage primary and secondary pollutants within the city.

Characteristics and sources of volatile organic compounds (VOCs) were investigated with highly time-resolved simultaneous measurements by two proton-transfer-reaction time-of-flight mass spectrometers (PTR-ToF-MS) at an urban and a suburban site in New Delhi, India, from January to March 2018. During the measurement period, high mixing ratios of VOCs and trace gases were observed, with high nocturnal mixing ratios and strong day–night variations. The positive matrix factorization (PMF) receptor model was applied separately to the two sites, and six major factors of VOCs were identified at both sites, i.e., two factors related to traffic emissions, two to solid fuel combustion, and two secondary factors. At the urban site, traffic-related emissions comprising mostly mono-aromatic compounds were the dominant sources, contributing 56.6 % of the total mixing ratio, compared to 36.0 % at the suburban site. Emissions from various solid fuel combustion processes, particularly in the night, were identified as a significant source of aromatics, phenols and furans at both sites. The secondary factors accounted for 15.9 % of the total VOC concentration at the urban site and for 33.6 % at the suburban site. They were dominated by oxygenated VOCs and exhibited substantially higher contributions during daytime.