Sriroop Chaudhuri

Elevated ambient particulate matter levels have become a critical urban sustainability concern in India, endangering health and well‐being (UN SDG 3) of a vast section of the population. We present an exploratory seasonal analysis (ESA) of the ambient PM _2.5 and PM ₁₀ concentrations, for nine Indian cities, using daily archival records from the Central Control Room for Air Quality Management (CAQM) for 2023. The ESA results revealed distinct seasonality in both PMs, varying as post‐monsoon (most polluted) > winter > summer > monsoon (cleanest). The National Capital Region (NCR: Delhi, Gurugram, Noida) appeared the most vulnerable to PM pollution, with Delhi as the most polluted among the nine cities, while Varanasi, the cleanest. Jaipur and Ahmedabad revealed concerns over windblown dust in summer, elevating the PM ₁₀ risks. Seasonal PM _2.5 /PM ₁₀ ratios indicated that besides fuel combustion in general, there is need for more location‐specific air quality control mechanisms, addressing local sources. For each city, about 9%–10% of the days appeared as “outlier”, representing sudden high spikes in PM levels. Both PMs exceeded the WHO health safety thresholds for about 90%–95% of days, even during monsoon, while for 99–100% of the days in winter and post‐monsoon times indicating year‐round public health concerns. Hierarchical Clustering (HCA) offered a spatio‐temporal (city‐season) PM _2.5 ‐vulnerability ranking scheme comprising of four statistically distinguishable clusters: Cluster 1 (148.67 ± 17.94 µg.m ⁻³ ) > Cluster 3 (79.469 ± 1.51 µg.m ⁻³ ) > Cluster 4 (59.90 ± 6.31 µg.m ⁻³ ) > Cluster 2 (32.64 ± 7.24 µg.m ⁻³ ). Cluster 1 represented the NCR cities for post‐monsoon and winter, while cluster 2 included all nine cities for monsoon and summer. Overall, HCA outputs could help setting up a joint action plan, bringing together various city municipal bodies to address the PM pollution. Applying Multiple Linear Regression (MLR) to the HCA clusters individually, revealed significant ( p < 0.05) statistical associations between meteorological parameters and PM2.5 concentrations in HCA clusters 1 (R ² : 0.76) and 3 (R ² : 0.67), while significantly lower for clusters 4 (R ² : 0.52), and negligible for Cluster 2 (R ² : 0.39). In Cluster 1 and 3, relative humidity and rainfall (monsoon season) exhibited strong inverse statistical relationships with PM _2.5 levels, consistent with potential scavenging and wet deposition processes to reduce the PM _2.5 risks, which was aggravated during post‐monsoon and winter. The latter occurred due to atmospheric stagnation (low wind speed, low solar radiance, cooler temperatures) that trapped the PM _2.5 near the ground. Meteorological influences, however, were minimal for HCA cluster 2 (R ² : 0.39), indicating importances of other factors (e.g., built‐up types and geometry; emission sources types, vegetation type and density) that need to be researched further. In the final sections, we reflect on a future vision about reimagining the urban transport sector, aligning policies with UN SDGs 7 (clean energy), 9 (infrastructure, and innovation) 16 (institution building) and 17 (forging multi‐sectoral partnerships) to address the particulate pollution crises.

Rapid urbanization across global South megacities has accelerated the overexploitation of urban aquifers, creating complex socio-hydrological crises that threaten long-term water resilience for a vast population. Conventional urban-water management frequently relies on uniform, city-wide regulatory mandates that fail to account for localized hydrogeological heterogeneities and the socio-economic drivers of private extraction. This study performed a seasonal assessment (post- and pre-monsoon) of groundwater levels (GWLs), across the National Capital Territory of Delhi, India, using a 13-year archival dataset (2010–2022) of 77 ‘common’ wells, with a sequential spatial–statistical framework. No statistically significant ‘seasonality’ was found in GWLs, except for isolated years. About 13% of the observations appeared as ‘deep outliers’, the call for more process-level hydrogeologic investigations. Spatial interpolation via the Inverse Distance Weighting (IDW) interpolation technique, alongside Global Moran’s I, Local Indicators of Spatial Association (LISA), and spatially Constrained Hierarchical Cluster Analysis (sHCA), revealed a recurrent spatial pattern: persistent, deep GWLs, within the fracture-dominated, low-yielding Alwar Quartzite (Delhi Ridge) of South and Southeast Delhi. The spatial clustering demonstrates the migration of the deep-GWL hotspots toward the unconfined alluvial aquifers of the Yamuna River floodplains to the east, threatening future baseflow stability. These spatial drawdown patterns represent a structural response to municipal Drinking Water Services Framework (DWSF) deficits, where intermittent supply and informal water markets incentivize the growth of more unregulated and unrestricted private pumping of groundwater. Achieving sustainable urban groundwater governance requires replacing blanket administrative mandates with a more data-driven, micro-zoned socio-hydrological framework across the city—combining area-specific extraction caps, economic instruments for geologically targeted aquifer storage and recovery, informal market regulation, and facilitating more participatory, community-based (Water users Associations, WUA) initiatives in the future to protect groundwater resources in Delhi. However, it requires specialized monitoring data, which is still largely lacking, and detailed investigations involving the aquifer hydrogeology and groundwater pumping patterns.

Active biomonitoring using moss bags provides a cost-effective alternative to traditional sensor-based air quality networks, directly supporting multiple UN Sustainable Development Goals, including SDGs 3, 7, 11, and 13. However, the reliability of moss bag outputs is frequently challenged due to the wide-ranging variability in moss bag construction and exposure. To critically evaluate these disparities, this scoping review employed the PRISMA framework to synthesize 137 moss bag studies between 2005 and 2025 to assess the dominant moss bag parameter choices. The results revealed a ubiquitous lack of a “standardized operating protocol (SOP)” in almost every aspect of moss bag studies, which restricts the replicability of experiments. The preparatory stages revealed widespread “customization” of moss sampling methods; the use of water as the main moss cleaning–washing medium (~87% of the literature reviewed herein); drying at 105 °C (~80.7%); and a general preference for the Sphagnum species (74%). Regarding the constructional phases, preferences for cylindrical bag shapes (60% of the literature reviewed herein) and nylon mesh for the bag material (68%) were noted. However, the mesh aperture sizes (10 mm²) and bag exposure duration (10 weeks) exhibited ranges far too broad for cross-study replication. Less than 10% of the literature explicitly mentioned choices of moss packing density, bag elevation, irrigation, shading, and orientation. Reflections on the influences of environmental/meteorological variables on moss bag results were sparse. Less than 5.5% of the literature delved into any process-level discourses for parameter choices, while barely 2.8% of the literature attempted to establish SOPs for moss bags. Overall, this study highlights that much remains to be learned about the moss–pollutant interaction pathways, phytotoxicity, and chlorophyll damage, and that moss bag studies still need to be streamlined; they still lack clarity in their reporting of study designs/parameterization choices, which could collectively limit the future use of moss bags to support air quality policy and decision-making.

In this study we offer an overview of the winter air quality (October 1–December 31, 2024) in Kolkata, one of the largest and most populous megacities of India and the world, using archival records of the Central Control Room for Air Quality Management System for particulate matter (PM _2.5 and PM ₁₀ ), carbon monoxide (CO), nitrogen dioxide (NO ₂ ), sulfur dioxide (SO ₂ ), and BTEX (benzene, toluene, ethylbenzene, xylene) for seven real‐time monitoring stations. Results indicated significant ( p < 0.01) spatial variations in species distributions across the city. The highest median PM _2.5 levels were recorded at the Bally station (80.80 µg cm ⁻³ ) while the lowest at RBU (48.38 µg cm ⁻³ ). Median PM ₁₀ levels varied between 146.96 µg cm ⁻³ (Victoria) and 96.83 µg cm ⁻³ (RBU). The highest median NO ₂ levels were at FW (59.03 µg cm ⁻³ ) and the lowest at RBU (18.58 µg cm ⁻³ ). The highest median total BTEX level was at Jadavpur (85.73 µg cm ⁻³ ) and the lowest at Victoria (7.23 µg cm ⁻³ ). The Mann–Kendal test, coupled with Sen's slope estimator, indicated increasing ( p < 0.00001) PM, CO, and BTEX levels, indicating growing health threats towards the end of winter. The daily PM readings exceeded the World Health Organization (WHO) safety thresholds at all monitoring stations throughout November and December. Daily benzene levels exceeded the safety threshold at Jadavpur and RSV for over 95% of days in November and December. Week‐wise exceedance analyses indicated greater concerns for the weekdays than weekends. Use of T:B ratios indicated a wide variability in BTEX sources across the stations, ranging from fuel combustion to vehicular exhausts to industrial emissions, to more mixed signatures, which call for more targeted approaches (e.g., positive matrix factorization, PMF) for BTEX source apportionment. Moreover, we noticed a significant “temporal shift” over time, with the T:B ratios dropping significantly in December (coal/biomass combustion). Spearman rank correlations revealed a significant (0.05 < p < 0.01) species assemblage, involving the PMs, CO, and total BTEX, implying their similar origin (e.g., vehicular exhaust), with stronger associations in December than October. We identified a significant pollutant‐weather nexus, including negative influences of relative humidity (0.05 < p < 0.01), air temperature ( p < 0.05) and solar radiance ( p < 0.05) on pollutant concentrations that undermines multiple UN Sustainable Development Goals (UN SDGs). We conclude by identifying future research areas while pondering over policy mechanisms ( Clean Air Action Plan, CLAAP ). The latter hinges on a participatory action network, melding the social, technological, economic, and institutional machinery of urban environmental protection.

The beneficiary roles of trees as natural air purifiers have been known for a long time, that goes into sustainability planning (e.g., health and well‐being , UN‐SDG 3; resilient cities and communities , UN‐SDG 11; life on land , UN‐SDG 15). In this reflective article, however, we ask: Trees Help, But What Goes With The Trees? In other words, trees can intercept, capture, and remove a variety of airborne pollutants, but how does that impact the trees? We scan the world literature ( N = 89) to summarize our experience about two pollutants: particulate matter (PM _2.5 , PM ₁₀ ) and ozone (O ₃ ). While we reflect on our state of knowledge about plant‐pollutant interactions, we also highlight the gaps in our current understanding that call for more research. In the process, we highlight changes in various biomolecules (e.g., reactive oxygen species (ROS), proline, and soluble sugars) that accumulate/deplete within plant cells in response to pollutant stress. In the final part of the narrative, we reflect on how our understanding of plant stress could be put to better use—for example, strategic use of plants in sustainable urban planning and development. Here, we discuss current practices around two of the most widely used indicator variables to assess plant stress—air pollution tolerance index (APTI) and anticipated pollution index (API). As we reflect on the significance of each, we discuss the world experience around “tolerant” and “sensitive” species, with the latter being used as air quality biomonitors . For urban applications (tree‐mediated pollutant removal), we emphasize the need to understand the characteristics of the target environment (e.g., street canyon vs. open road; local wind speed and direction) to decide on specific leaf traits, road‐side planting patterns. Overall, we envision more process‐level research to unravel the context‐specific plant‐pollutant interaction pathways (e.g., by different built environment types, local meteorological conditions, and pollutant sources) for the concerned urban authorities to use the information more strategically in developing efficient pollution control interventions.

Dual concerns involving the rise in airborne pollutant levels and bulging need to protect-preserve human health have propelled the search for innovative means for air quality monitoring to aid in evidence-based decision-making (pollution prevention-mitigation). In this regard, moss bags have gathered a great deal of attention as active biomonitors. In this reflective discourse, we systematically review the world literature to present a bird’s eye view of moss bag applications and advances while highlighting potential concerns. We begin with a brief note on mosses as biomonitors, highlighting the advantages of moss bags over the passive technique (native moss), other living organisms (lichens, vascular plants), and instrument-based measurements. A major strand of moss bag research involves urban ecosystem sustainability studies (e.g., street tunnels and canyons, parks), while others include event-specific monitoring and change detection (e.g., SARS-CoV-2 Lockdown), indoor-outdoor air quality assessment, and change detection in land use patterns. Recent advances include biomagnetic studies, radioisotopic investigations, and mobile applications. Efforts are currently underway to couple moss bag results with a suite of indicators [e.g., relative accumulation factor (RAF), contamination factor (CF), pollution load index (PLI), enrichment factor (EF)] and spatially map the results for holistic appraisal of environmental quality (hot spot detection). However, while moss bag innovations and applications continue to grow over time, we point to fundamental concerns/uncertainties (e.g., lack of concordance in operational procedures and parameterization, ideal species selection, moss vitality) that still need to be addressed by targeted case studies, before the moss results could be considered in regulatory interventions.

India is a global hotspot for irrigation-induced groundwater withdrawal, leading to widespread lowering of water levels, in turn resulting in disproportionate access to irrigation supplies among farming communities. Efforts to mitigate the situation, however, have fallen short, largely due to technocentric vision (e.g. microirrigation adoption) of the regulatory authorities (RAs), which does little to integrate the vast groundwater-dependent socioecologies with the decision making system. In view of that, we invite the RAs to deliberate upon a cap-and-trade mechanism that proposes to mobilize the farmers at every aspect of planning and execution, while to tackling multiple challenges simultaneously: (a) restrict groundwater pumping to a pre-defined safe level (cap), (b) creating a shared space/quotas for all to pump (allocation); and (c) making provisions for trade of allocations. The latter further augments farmers’ access to groundwater (and irrigation). Using a systematic bibliometric analysis of relevant world literature and contextual appraisal of groundwater-irrigation landscape in India, we develop a conceptual framework of cap-and-trade in three parts. In the first Pre-implementation stage, we emphasize a reality check study to assess ground conditions, if favorable for a cap-and-trade approach (existing social, economic, institutional circumstances). Next, in the Implementation stage, (1) we recommend an integrated hydrogeological-hydrometeorological modeling to determine flexible capping arrangements, with the possibility of delineating certain priority regions (coastal ecosystems); (2) for allocations, a reasonable fraction of the cap over a defined period; we envision a thoroughly participatory arrangement, centering on four action areas: identifying, informing, consulting, and involving the farmers, alongside all stakeholders engaged in the groundwater-irrigation decision making; (3) for trade, we urge the RAs to create win-win situations for both the sellers and buyers; develop the transaction protocols on certain foundational principles (e.g. simplicity, transparency and consistency); strengthening of local institutions, and development of targeted financial support schemes. We consider the third part of the narrative, Post-implementation stage, as a real game changer, comprising of a monitoring, auditing (performance benchmarking) component coupled with multitiered outreach-mentoring drives that demonstrate to the farmers the benefits of becoming part of the cap-and-trade program. Overall, a main motivation to present this research is to shatter the age-old socio-cognitive beliefs/taboos around groundwater pumping (My land, My Water), breaking the hegemony of the water sellers (rich/wealthy large landholder clans), to potentially, create a social norm whereby the farmers realize the value of restricting groundwater pumping and sharing for mutual prosperity.

Uninhibited drafting and plummeting groundwater levels have entailed a slew of eco-environmental and socio-economic crises across vast swathes of South Asia, leading to social turmoil over the demand-supply gap in the irrigation sector. We adopted a mixed-method approach, combining systematic bibliometric assessment with contextual analysis, to highlight to the regional water authorities (RWAs) the core tenets of groundwater markets (GWMs), already operating in various capacities and forms in different parts of South Asia, as a potential option to address the crisis. GWMs, occurring along a farmer-water-irrigation continuum, have mixed impacts on groundwater-dependent socio-ecologies, ranging from beneficial to counter-productive. Given the dire projections of groundwater depletion in the near future and the inadequacy of the state machineries to meet surging irrigation demand, a critical policy question that we approached in this narrative was: Can GWMs be institutionalized as a regulatory tool for ‘supply-side’ management of irrigation resources? To that end, we helped RWAs grow a deeper understanding of the complexity and interdisciplinarity associated with the vast network of actors and agencies interlocked within GWMs. By the same token, we urged the RWAs to consider a collective space—potentially in the form of a groundwater users’ association (GWUA)—as a prerequisite to imagining GWMs in an institutional mould. We present a critique of current world experiences with GWUAs and reflect on the socio-environmental barriers to establishing a functional GWUA. We outline tentative means for RWAs to build credibility and increase acceptability of GUWAs at the grassroots, including capacity building, value-based standard operating procedures and harnessing solidarity and social responsibility. In conclusion, we offer RWAs a simple system of a ‘reality’ check, to evaluate the ground conditions and feasibility of contemplating GWMs in the first place.

Land degradation and desertification (LDD) has gained worldwide policy attention due to decline in land quality and the resultant economic burden accrued upon a vast population reliant on land-based natural capital. In India, the impacts are becoming apparent as 24 out of 29 states have been experiencing LDD since the early 2000s. Here, we adopt a mixed-method approach combining hierarchical cluster analysis (HCA) and multilinear regression analysis (MLRA) with contextual assessments to draw on, using state-level information from 2011–2013, an age-old question: do farming operations aggravate LDD? The HCA identified 11 states that currently lead the trajectory with the highest state-wise percentages of LDD areas under ‘water erosion’, ‘salinity’, and ‘water logging’, which are the three most widely reported impacts of farming practices on land systems’ sustainability as apparent in the relevant LDD literature. MLRA of the 11-state cluster revealed that state-wise NPK fertilizer-application rates (p < 0.01); number of moldboard ploughs (p < 0.01); net irrigated area (p < 0.01); groundwater-sourced irrigation (p < 0.05); and multiple cropping practices (p < 0.01) exacerbate LDD, while bio-pesticides (p < 0.05) and zero-till drills (p < 0.01) do the opposite. In recent years, the government has introduced several improved measures, such as nutrient-based subsidies (NBS) and integrated nutrient management (INM), to help farmers optimize agrochemical applications, thus moving from traditional practices (input intensive) to a more land-conservation-centric approach. However, at the cognitive level, farmers are unsure/unaware of the benefits. Moreover, due to various institutional weaknesses, lack of sensitization, extension services, capacity building, incentives, and certain inherent flaws in these newer strategies, their uptake remains low, while traditional practices continue at the grassroots. We attempt to broaden the regulatory purview by reflecting on the DPSIR framework (Driver–Pressure–State–Impact–Response), highlighting the role of indirect drivers of LDD that largely influence farmers’ preferences for certain practices. In the final section, we emphasize the need for a data revolution to support process-level research to be able to devise more informed and targeted LDD control–abatement strategies, which is currently largely absent.