Search

Energy efficiency plays a central role in climate change mitigation policies. Countries are using different methods to estimate energy savings from energy efficiency improvements. Improved methods to measure energy efficiency savings are adopted mainly in countries with mandatory energy efficiency targets. They use bottom-up and top-down methods to enhance the reliability of savings estimates. India has implemented various energy efficiency measures, and the impact of most of the schemes is estimated using the simplified deemed savings bottom-up approach. Index Decomposition Analysis is a top-down approach, but its use in India is limited due to a lack of reliable national energy balances. This study uses India's energy balances from International Energy Agency to estimate the energy efficiency savings in India during 2011–19. It is found that the IDA estimates are lower than the government's deemed savings estimates. The underlying assumptions in the simplified deemed savings approach may overestimate savings, or savings from index decomposition analysis may be underestimated due to data limitations. Improved methods and reliable and timely data is essential for measuring energy savings from energy efficiency. National-level targets on energy efficiency can push improvements in energy savings measurement techniques. The targets can also address several barriers in the energy efficiency markets. • Developing countries use simplified approaches to estimate EE savings. • Combination of bottom-up and top-down approaches increase reliability of estimates. • IDA estimates of saving from EE policies in India are lower than government estimates. • Energy intensity targets can improve energy savings measurement techniques in India. [ABSTRACT FROM AUTHOR]

The emerging economies of Brazil, Russia, India, China and South Africa (BRICS) have significant influence on the global economic and environmental trajectories. They have carbon intensive economic systems, which contribute significantly to total global greenhouse gas (GHG) emissions, leading to climate change. However, BRICS have joined the race to net-zero emissions by 2050 in the quest for a climate neutral and sustainable global economy. The journey, however, is not without challenges and opportunities. The proliferation of the coronavirus disease 2019 (COVID-19) had mixed reactions from scientists regarding its implications on net-zero trajectories. While statistical data show a correlation between COVID-19 and a decrease in total emissions, it is envisaged that COVID-19 compromised the efforts to develop carbon neutral economies. Hence, there is still need for more scientific examination of COVID-19's impact on net-zero ambitions, especially in the emerging economies. This study focuses on India and South Africa's trajectories. Statistical analysis of secondary data from authentic interactive web-based dashboards for COVID-19 data repositories, namely Our World in Data and Climate Action Tracker was performed in conjunction with the document analysis approach following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. Some of the COVID-19 challenges as indicated by the results of the study include curtailing the technology transfer staircase in the energy sector, retaliatory emissions for recovery and resource diversion. The opportunities presented by COVID-19 in the quest for carbon neutrality include behavioural changes in investment, production and consumption patterns with a focus on low carbon options. Governments and stakeholders need to focus on addressing the barriers whilst riding on the opportunities presented by the pandemic to achieve net-zero emissions by 2050. [ABSTRACT FROM AUTHOR]

COVID-19 is a severe acute respiratory syndrome caused by the novel coronavirus SARS-CoV-2. The COVID-19 pandemic lockdowns and quarantines have led to significant industrial slowdowns among the world's major emitters of air pollutants, with resulting decreases to air pollution and greenhouse gas emissions in nations such as China, India and US, deemed to be major sources of global CO 2 emissions, as well. However, there are major concerns that these decreases in atmospheric pollution can be hampered as economies are reactivated. Historically, countries have weakened environmental legislations following economic slowdown to encourage renewed economic growth. Such a policy response now will likely have disproportionate impacts on global Indigenous people and marginalized groups within countries, who have already faced disproportionate impacts from COVID-19 and environmental pollution. Our "new normal" remain nimble enough to allow us to fine-tune our interventions, research tools and solutions-oriented research to quickly enough to stay ahead of the pandemic trajectory in the face of air pollution and climate change. Societal and behavioral changes to reduce these anthropogenic cumulative stressors should be advocated, while prioritizing the public health of marginalized groups around the world, promoting new approaches to champion environmental health along with educational programs addressed to the population. Bold government decisions can restart economies while pre-empting future inequities and committing to environmental protection in an era of COVID-19 and global change. [ABSTRACT FROM AUTHOR]

Tropical coastal wetlands have been well recognized for their role in mitigating climate change apart from possessing high biodiversity values as well as providing important habitats for fisheries and other ecosystem services. Although these wetlands play key roles in sequestering carbon (C) in the lithosphere and hydrosphere, there is a notable dearth of comprehensive yet spatially explicit accounts of their total blue carbon (TBC) stocks. The anthropogenic factors including development stressors have fundamentally altered the global C dynamics. In this respect, holistic accounting of the total C stocks of the coastal wetlands becomes the foremost task in emphasizing their recognition as integral components of climate change mitigation strategies. This study modeled TBC stocks of an intertidal mudflat of eastern India across different land use/ land covers (LULCs) by quantifying the above ground biomass (AGB), below ground biomass (BGB), and soil organic C (SOC). The distribution of SOC was modeled through spatial interpolation of point-specific C densities (R2 = 0.77; RMSE = 22.91 Mg ha−1). AGB was estimated by establishing allometric relationships between geospatial data, both of active (PALSAR-2) and passive (Pleiades-1B) nature and in-situ dendrometric variables using the artificial neural network (R2 = 0.85; RMSE = 48.91 Mg ha−1). BGB was estimated from the modeled AGB. Spatial integration of these datasets estimated the TBC stock of mudflat as 27,469.30 Mg. Overall, open mangrove represented highest mean TBC density (163.29 Mg ha−1) while herbaceous vegetation recorded largest TBC stock (9818.94 Mg). Mean TBC densities across LULCs were significantly different (p < 0.05) from each other except for the herbaceous vegetation and built-up categories, indicating the inertial effects of paleo-land covers. Accordingly, this study could be inferred as a pioneering one in developing a comprehensive geospatial model of TBC accounting in India towards strengthening the regional and national C inventories. [Display omitted] • Total blue C stocks of an intertidal mudflat including AGB, BGB and SOC estimated • Applying destructive/non-destructive sampling, elemental analysis and RS datasets • Coupling of fine resolution multispectral and SAR datasets through ANN • Effects of land use/land cover patterns on blue C dynamics assessed [ABSTRACT FROM AUTHOR]

The bioeconomic potential of monopodial and sympodial bamboos is not well understood. Therefore, Net primary productivity (NPP), total biomass, carbon (C) stock, soil organic carbon (SOC), CO 2 sequestration, and bioenergy potential were studied in a sympodial Chimonocalamus griffithianus and a monopodial Phyllostachys mannii bamboo in Meghalaya, north-eastern India. P. mannii stand with mean culm density 16,877 ha−1, height 14.8 m and diameter 4.4 cm, accumulated 107.56 Mg ha−1 biomass with a total NPP of 18.83 t ha−1yr−1. It stored 50.67 Mg C ha−1 in biomass, 77.28 Mg C ha−1 in soil, and had sequestration potential of 469.58 t CO 2 ha−1. C. griffithianus stand with mean clump density 1065 ha−1, mean culm density 52,185 ha−1, height 7.19 m and diameter 3.04 cm, accumulated 67.08 Mg ha−1 biomass with a total NPP of 15.30 t ha−1 yr−1. It stored 31.30 Mg C ha−1 in biomass, 83.25 Mg C ha−1 in soil, and had sequestration potential of 420.40 t CO 2 ha−1. Matured culms (>2–3 years old) of P. manni and C. griffithianus produced 143.08–166.65 MW h and 87.13–101.48 MW h of energy per ha, respectively. Although landuse history and site characteristics of the two stands were not 100 % identical, significantly greater (p < 0.05) standing biomass, NPP, growth rate, carbon sequestration potential, and energy values of P. mannii than C. griffithianus makes the monopodial bamboo a better choice for energy plantation and climate change mitigation tool than the sympodial. • Monopodial bamboo, Phyllostachys mannii , surpasses sympodial Chimonocalamus griffithianus in bioeconomic potential. • P. mannii exhibits higher biomass, NPP, carbon sequestration, and energy values. • Comparative analysis reveals the superior suitability of monopodial bamboo for energy plantations. • Results provide valuable insights for sustainable development in India's biobased economy. • Study contributes to understanding the role of bamboos in mitigating climate change. [ABSTRACT FROM AUTHOR]

Accurately assessing forest fire susceptibility (FFS) in the Similipal Tiger Reserve (STR) is essential for biodiversity conservation, climate change mitigation, and community safety. Most existing studies have primarily focused on climatic and topographical factors, while this research expands the scope by employing a synergistic approach that integrates geographical information systems (GIS), remote sensing (RS), and machine learning (ML) methodologies for identifying and assessing forest fire-prone areas in the STR and their vulnerability to climate change. To achieve this, the study employed a comprehensive dataset of forty-four influencing factors, including topographic, climate-hydrologic, forest health, vegetation indices, radar features, and anthropogenic interference, into ten ML models: neural net (nnet), AdaBag, Extreme Gradient Boosting (XGBTree), Gradient Boosting Machine (GBM), Random Forest (RF), and its hybrid variants with differential evolution algorithm (RF-DEA), Gravitational Based Search (RF-GBS), Grey Wolf Optimization (RF-GWO), Particle Swarm Optimization (RF-PSO), and genetic algorithm (RF-GA). The study revealed high FFS in both the northern and southern portions of the study area, with the nnet and RF-PSO models demonstrating susceptibility percentages of 12.44% and 12.89%, respectively. Conversely, very low FFS zones consistently displayed susceptibility scores of approximately 23.41% and 18.57% for the nnet and RF-PSO models. The robust mapping methodology was validated by impressive AUROC (>0.88) and kappa coefficient (>0.62) scores across all ML validation metrics. Future climate models (ssp245 and ssp585, 2022–2100) indicated high FFS zones along the northern and southern edges of the STR, with the central zone categorized from low to very low susceptibility. Boruta analysis identified actual evapotranspiration (AET) and relative humidity as key factors influencing forest fire ignition. SHAP evaluation reinforced the influence of these factors on FFS, while also highlighting the significant role of distance to road, distance to settlement, dNBR, slope, and humidity in prediction accuracy. These results emphasize the critical importance of the proposed approach for forest fire mapping and provide invaluable insights for firefighting teams, forest management, planning, and qualification strategies to address future fire sustainability. • Evaluated 44 factors, including climate, topography, and human impact. • Applied ML models, identifying high susceptibility in northern and southern STR. • Projected high susceptibility zones under ssp245 and ssp585 scenarios. • AET and humidity crucial for forest fire ignition; SHAP analysis confirmed. • Distance to road, settlement, dNBR, slope, and humidity impact prediction. [ABSTRACT FROM AUTHOR]

Agroforestry, a sustainable land-use system that integrates trees with crops and/or livestock, is recognized as an effective strategy for synergizing climate change adaptation and mitigation efforts in India. However, the prevalence of limited land under agroforestry indicates the presence of significant constraints hindering its widespread implementation. To address this challenge, the State Action Plan on Climate Change (SAPCC) represents a potentially potent policy tool for driving the expansion of agroforestry at the sub-national level. The aim of this study was to examine (i) how the SAPCCs recognized and reported the benefits of agroforestry for climate change adaptation and mitigation, and (ii) what policy approaches are put forth to operationalize agroforestry in India. For this study, the information on agroforestry was coded using a hybrid approach (a combination of deductive and inductive coding) followed by thematic analysis and peer debriefing (for validation of the generated codes and themes). Many of the mitigation and adaptation benefits of agroforestry are reflected in the SAPCCs. However, the predominant focus of these SAPCCs has been on tree-based agroforestry, with insufficient attention given to the crop-tree-livestock nexus, which could offer greater scope for reducing agricultural emissions. Furthermore, existing constraints to the expansion of agroforestry have not been adequately addressed, and the strategies proposed lack the necessary precision to enable effective implementation on the ground. These shortcomings are further compounded by the absence of accurate budgetary estimates, thereby hindering the ability to execute meaningful actions at the grassroots level. The results of this study could offer valuable perspectives on how the potential benefits of agroforestry may be harnessed more prudently to realize mitigation and adaptation outcomes in India while aligning with the country's Nationally Determined Contributions and building sustainable livelihood. [Display omitted] • India's sub-national climate change action plans acknowledge agroforestry's potential for climate change adaptation and mitigation. • However, the plans primarily focus on adding trees to expand agroforestry and overlook the potential of agrosilvopastoral systems. • The existing constraints of agroforestry adoption in India are not sufficiently addressed, and budget estimates vary significantly among states. • To address these issues, the plans require revision to incorporate specific actions and a clear implementation roadmap. [ABSTRACT FROM AUTHOR]

Crop residue burning is a common practice in many parts of the world that causes air pollution and greenhouse gas (GHG) emissions. Regenerative practices that return residues to the soil offer a 'no burn' pathway for addressing air pollution while building soil organic carbon (SOC). Nevertheless, GHG emissions in rice-based agricultural systems are complex and difficult to anticipate, particularly in production contexts with highly variable hydrologic conditions. Here we predict long-term net GHG fluxes for four rice residue management strategies in the context of rice-wheat cropping systems in Eastern India: burning, soil incorporation, livestock fodder, and biochar. Estimations were based on a combination of Tier 1, 2, and 3 modelling approaches, including 100-year DNDC simulations across three representative soil hydrologic categories (i.e., dry, median, and wet). Overall, residue burning resulted in total direct GHG fluxes of 2.5, 6.1, and 8.7 Mg CO 2 -e in the dry, median, and wet hydrologic categories, respectively. Relative to emissions from burning (positive values indicate an increase) for the same dry to wet hydrologic categories, soil incorporation resulted in a −0.2, 1.8, or 3.1 Mg CO 2 -e change in emissions whereas use of residues for livestock fodder increased emissions by 2.0, 2.1, or 2.3 Mg CO 2 -e. Biochar reduced emissions relative to burning by 2.9 Mg CO 2 -e in all hydrologic categories. This study showed that the production environment has a controlling effect on methane and, therefore, net GHG balance. For example, wetter sites had 2.8–4.0 times greater CH 4 emissions, on average, than dry sites when rice residues were returned to the soil. To effectively mitigate burning without undermining climate change mitigation goals, our results suggest that geographically-target approaches should be used in the rice-based systems of Eastern India to incentivize the adoption of regenerative 'no burn' residue management practices. • Efforts to build SOC for climate change mitigation, while simultaneously avoiding burning, may have unintended consequences. • Tier 1, 2, and 3 modelling approaches were used to compare no-burn rice residue pathways. • Field hydrology had a dominant effect on methane emissions. • Soil incorporation of residues increased emissions relative to open burning, except in comparatively dry fields. • Biochar is estimated to have the lowest GHG emissions of the evaluated 'no burn' alternatives. [ABSTRACT FROM AUTHOR]

• Four design principles would inform a forest carbon market-based mechanism in India. • Robust governance and accounting emerge as key technical considerations. • Local community involvement and flexible spatio-temporal criteria would encourage participation. • Land tenure, implementation challenges and design flaws may inhibit effectiveness. Forest carbon markets (FCMs) have emerged as a significant means to direct resources toward urgent climate action that can mobilize a large set of actors and catalyze funding toward reducing deforestation and promoting sustainable forest management. Here, we conduct a critical qualitative review of global academic and investigative literature to identify ten major sets of design principles that provide a platform for the functioning of carbon markets worldwide. From these, we pinpoint four design principles which may be relevant to future market-based mechanisms in India We propose that clarity over market-quality standards, comprehensive regulatory framework, minimization of transaction costs and upfront financing options, and flexibility in time-bound and spatial commitments would be fundamental to ensure that market-based mechanisms in India accrue sustainable and long-term benefits to climate action and human well-being. A successful market-based mechanism in India's forestry sector would have to overcome challenges around land property rights, local implementation capacities and knowledge gaps, and incentive structures to ensure that it likely caters to the needs of all stakeholders while delivering socio-ecological benefits. [ABSTRACT FROM AUTHOR]

To better understand forest carbon budgets and design forest-based climate change mitigation solutions, reliable biomass estimation is critical. Integrating multi-sensor remote sensing data can improve forest monitoring and evaluation. This study adopted a one-hectare plot size sampling design to improve the integration of GEDI footprints with in-situ, optical, and SAR data for the estimation of forest above-ground biomass (AGB). The study was carried out for a managed tropical forest in the Himalayan foothills of India. The space-borne GEDI retrieved the canopy height of the study area with an RMSE of 3.36 m and Adj. R2 of 0.70. Extrapolating GEDI footprint heights (RH95) with Landsat 8 indices using Random Forest (RF) yielded a spatial canopy height of the study area with an R2 of 0.97 and RMSE of 2.32 m. Using the GEDI canopy height, foliage density, and plant area index, the AGB at GEDI footprints level was estimated using RF, with an R2 of 0.91 and an RMSE of 20.10 Mg ha−1. The spatial AGB model that only considered ALOS-2 SAR variables had an R2 of 0.61 and an RMSE of 18.27 Mg ha−1, whereas the RF model that considered both SAR variables and canopy height had a superior R2 of 0.77 and a lower RMSE of 13.86 Mg ha−1. The addition of canopy height data reduced the RMSE of the AGB model by 4.41 Mg ha−1 and also predicted a higher range of AGB. The study demonstrates the effectiveness of combining GEDI data with other sensors (optical and SAR data) to provide precise AGB of multistage managed forests using a one-hectare plot size sampling design. • One-hectare plot sampling design adopted to integrate GEDI, Landsat-8, and ALOS-2 SAR. • Random Forest algorithm used to predict canopy height and AGB. • Integration of canopy height with ALOS-2 SAR-derived variables improved AGB prediction and reduced AGB uncertainty. [ABSTRACT FROM AUTHOR]

• CAPs have emerged as key policy tools for cities to fight impacts of climate change. • Existing coverage on city CAPs is lacking in case of developing countries. • Cities often have to fulfil multiple objectives, also including climate change. • Cities and local governments need more autonomy for effective climate action. • Climate policy formulation at local levels may avoid experimentation and influence. Climate change impacts have affected cities across the world, with cities in the developing world showing higher climate risks to property, infrastructure, and individual lives. Climate Action Plans (CAP) have emerged as a key tool and policy strategy for cities globally in their fight against climate change. However, most studies on CAPs cover cities of the Global North, lacking representation of the developing world. This study conducts an exploratory case study analysis of CAPs of four metropolitan cities in India, one of the world's worst climate-exposed cities. The objective is to highlight and compare key components and characteristics of these CAPs and showcase their key strengths, unique solutions, weaknesses, and areas of improvement that may offer opportunities for strengthening existing and future city CAPs leading to effective climate policy and urban governance at the national and global level. Characteristics of the CAPs are discussed under the purview of global best practices and frameworks, such as C40 cities. Analysis shows that city CAPs in India are at a nascent stage owing to the absence of climate policies resulting in experimentation and implementation, suiting stakeholder and local government needs. [ABSTRACT FROM AUTHOR]

Urban floods have become more frequent and devastating in recent decades. Low impact developments (LIDs) have gained wide acceptance as a more sustainable and effective technique for mitigating urban flooding. This study examines the hydrological control effects of LIDs on mitigating runoff depth and peak runoff in the context of climate change for four micro-watersheds (A, B, C and D) in northeast India. In addition, attempts have been made to determine whether redesigning the existing drainage helps reduce runoff in the study area. Results show that redesigning the drainage system has resulted only in 2.5–3.6% reduction in runoff depth for the four micro-watersheds. LIDs were effective in managing the stormwater in all four micro-watersheds. Among the four LIDs considered (green roof, permeable pavements, infiltration trenches, and rain barrels), the green roof showed the highest percentage reduction in runoff characteristics. Climate change analysis has shown a significant increase in the runoff characteristics in all four watersheds. For watersheds A, B, C, and D, the green roof effectively reduced runoff by 30%–38%, 83%, 50%, and 34%, respectively. This study will help the decision-makers to assess and choose the best LIDs to minimize the risk of flooding. • Effectiveness of LID in runoff mitigation under climate change was studied • Climate change has increased the rainfall intensities and runoff in the study area • Green roof was found to be effective in runoff reduction for the study area • The runoff coefficient was found to decrease after the implementation of LIDs [ABSTRACT FROM AUTHOR]

India has a significant importance in achieving the global Paris agreement's long-term goal as it is the world's third-largest consumer of energy. This paper aims to improve the understanding of the opportunities and constraints of decarbonizing India's electricity sector and adds to the growing body of literature by modelling the electricity sector in India with a dynamic optimization approach that assesses options for effective greenhouse reductions through carbon pricing. Attaining significant variable renewable energy penetration in India by 2050 is consistent with the lowest cost power generation options identified through our simulations, where solar and wind can provide 66 % of the electricity needs by 2050, even without a carbon price. With a carbon price of US$50/tCO2e, the simulations project that wind and power generation share in the electricity mix will rise to 81 %, leading to significant emission reductions. In this scenario, power sector emissions will be 164 million tCO2e by 2050, which is only about 14 % of the emissions levels in 2019. The analysis also indicates that fossil fuels remain part of India's electricity mix in 2050, but their role and operation would dramatically change. When a carbon price of US$50/tCO2e is introduced, coal capacity remains valuable to fill demand when solar and wind are not available. This would require modifications in operation schedules and repurposing coal power plants for frequent ramping up and down. [ABSTRACT FROM AUTHOR]

Large-scale tree planting has been advocated for decades in many countries as a cost-effective strategy to mitigate carbon, rejuvenate degraded landscapes, and support local livelihoods. Recent studies, however, suggest limited ecological and livelihood impacts of tree planting programs, indicating possible limits to tree planting as a natural climate solution. In this paper, we explore these carrying capacity-like limits by evaluating the site suitability of forestry landscapes of the northern Indian state of Himachal Pradesh using theory/expert-based rules and machine learning algorithms. We find that the state can only achieve a maximum of 31.54% forest cover due to socio-ecological and biophysical constraints, much less than India's goal of bringing 66% of the total geographical area of Himalayan states into forest cover. The low availability of suitable lands for growing trees, together with poor plantation site selection by forest range officers limit the use of tree planting as a sole climate mitigation strategy. To approach theoretical planting limits, we propose an ePSA (e-Plantation Site Assistant) recommendation system based on our site-suitability results to assist forest rangers in selecting suitable sites for planting trees. An initial deployment of the recommender system suggests its potential utility in shaping the long-term success of tree plantations as an effective carbon strategy in northern India and beyond. Overall, we argue that there is a need to realign over-ambitious national and international tree planting targets with actual limits from site characteristics to avoid massive wastage of funds and to obtain feasible carbon mitigation outcomes. [ABSTRACT FROM AUTHOR]

A large number of Indian thermal power plants are tied under power purchase agreements with distribution companies. However, the existing energy models do not account for these 'take or pay' contracts for investigating climate policies. In this context, this paper investigates the impact of these power purchase agreements on power sector operations, cost of electricity and emissions from the Indian power sector. An optimization model was developed for this study with 620 coal, 239 gas, 21 nuclear and 686 hydro units with technology and operational characteristics to analyze electricity dispatch for power sector. The operations of thermal power plants were analyzed with and without power purchase agreements, and low carbon policy scenario. The scenarios are compared for power plant operations, cost of electricity, stranded assets, and emissions. The results show that there is a significant cost advantage for plants covered under power purchase agreements which favors the operations of older inefficient power plants in baseline scenarios. In addition, the representation of power purchase agreements raises the cost of electricity by 26 percent. A change in operating strategy from least cost to least emissions with a lower demand growth scenario can mitigate 24 percent emissions. The cost of carbon abatement is 268–277 USD/tonne for policy scenarios. Options like renegotiation of power purchase agreements can be considered to mitigate emissions. • Indian power sector optimization model is formulated with power purchase agreements. • Older power plants have cost advantage under existing power purchase agreements. • Power contracts in existing models result in total cost escalation of 26 percent. • The power sector can reduce emissions by 24 percent with optimal operations under lower demand. • Existing projects in pipeline will result in large stranded assets. [ABSTRACT FROM AUTHOR]

Indian residences are vulnerable to heat-driven discomfort amid the mounting prevalence of weather extremes, residential design and construction practices, and densifying urbanscapes. Therefore, it is vital to understand the thermal comfort characteristics of nationwide residences. This study proposes an adaptive thermal comfort model based on yearlong field surveys in eight cities located across five climate zones of India – the India Model for Adaptive Comfort - Residential (IMAC-R). The model prescribes the operative temperature bands for 80% and 90% thermal acceptability in correlation with the outdoor reference temperature, applicable to mixed-mode (MM) and naturally ventilated (NV) residences. More than 80% of the Indian residential occupants experienced a neutral thermal sensation in the indoor operative range of 16.3–35 °C in response to a 5.5–33 °C variation in the 30-day outdoor running mean temperature. Comparing the proposed model with the PMV model revealed that the latter underpredicts the thermal adaptivity of Indian occupants. The model was also compared against its predecessor – India Model for Adaptive Comfort for Commercial Buildings (IMAC MM and NV), along with relevant global and regional thermal comfort models. On average, the neutral temperature prescribed by IMAC-R was warmer than the temperatures prescribed by IMAC MM and NV by 2.9 °C and 2.1 °C, respectively; it was also warmer than the temperature prescribed by the recent ASHRAE-55 and EN 16798-1 models by 2 °C and 0.3 °C, respectively. IMAC-R reserves the prospect of addressing the thermal comfort needs of the national population while paving the way for long-term energy savings and climate action. • An adaptive model is proposed for mixed-mode and naturally ventilated residences across the Indian climates. • Indian residential occupants are more adaptive than as predicted by ASHRAE-55, EN 15251, and PMV models. • Fan/window operation and change in clothing insulation were the key adaptive responses. • Comfort modelling is explored in correlation with Universal Thermal Climate Index. [ABSTRACT FROM AUTHOR]

Conventional rice-wheat cropping system (RWCS) in western Indo-Gangetic Plains (IGP) is carbon and energy intensive. A field experiment was conducted to evaluate energy budgeting, carbon footprints (CF) and greenhouse gas (GHG) emissions from RWCS under long-term tillage and residue management practices. Experiment consisted six treatment combination of tillage [conventional tillage (CT), reduced tillage (RT) and zero tillage (ZT)] and residue [with residue (+R) and without residue (–R)] namely (i) CT-R (conventional farmers' practice), (ii) CT + R, (iii) RT-R, (iv) RT + R, (v) ZT-R and (vi) ZT + R. Energy consumption ranged from 51.87 GJ ha−1 (ZT-R) to 64.91 GJ ha−1 (CT + R) and irrigation water was major energy intensive input (41–44%) followed by chemical fertilizer (32–40%). Compared to CT-R, energy use efficiency (EUE) increased by 8.7–22.4%, CF lowered by 77.9–34.3%, and GHG emission lowered by 12.8–16.3% in different treatments. Residue addition enhanced the soil carbon accumulation in ZT + R (1213 kg C ha−1 yr−1) and RT + R (987 kg C ha−1 yr−1). Overall, switching from CT–R to ZT + R lowered energy consumption (19%), GHG emission (16%) and CF (78%), making it best-bet option for climate change mitigation and global warming related environmental protection in western IGP and similar agro–ecologies. [Display omitted] • Energy use efficiency (EUE), Greenhouse gases (GHGs) emission and carbon footprints (CF) were analysed. • Irrigation water contribute maximum (41–44%) share of input energy followed chemical fertilizers (32–40%). • Conservation tillage and residue management enhanced energy productivity (15.8–21.0%) and EUE (17.1–22.4%). • The CF lowered by 77.9% in zero tillage with residue to 45.2% in reduced tillage without residue. • Zero tillage with residue addition is most energy efficient system with lower GHG emission and carbon footprint. [ABSTRACT FROM AUTHOR]

• Microclimatic effects of future urbanization on MMR were assessed by WRF-UCM model. • The temperature of suburban centers is likely to increase along with urbanization. • Future urbanization pattern will have negligible impact on wind speed. • By 2050, discomfort hours over newly urbanized area will increase by 3–5 h/day. • The cool roof/wall-based mitigation plan is able to curb the future temperature increase. This study examines the microclimatic impacts of future urbanization over the Mumbai Metropolitan Region (MMR) in India using a dynamic downscaling approach. Initially, two numerical experiments (curr_exp and fut_exp) were carried out by integrating 2018 and 2050 land-use/land-cover patterns under the same meteorological conditions. Afterwards, the spatial and temporal changes in surface air temperature, wind speed, and thermal discomfort were assessed by comparing the simulated results between curr_exp and fut_exp. To remediate the observed adverse microclimatic impacts of future urbanization, a mitigation strategy was designed and implemented in the third experiment (miti_exp). Simulation results show that the average maximum (minimum) surface air temperature of the region would increase by 1.41 °C (1.27 °C) due to future urbanization. However, if we adopt the mitigation strategy, this growth can be restricted to 0.69 °C (0.92 °C). In the context of thermal discomfort, an additional 20% of the total area can undergo hyperthermal treatment by 2050. This study reveals that although the implemented mitigation strategy can restrict the increasing temperature, it is ineffectual in minimizing the thermal discomfort level. The results of this study will be helpful in designing area-specific climate action plans through which goals of sustainable urban development can be accomplished. [ABSTRACT FROM AUTHOR]

Crop residue management remains a major problem in the Indian agriculture sector. The in-situ firing of crop residues has been linked to air pollution, global warming, soil fertility decline and others. Biochar conversion through slow pyrolysis could be one of the techniques for the safe disposal of crop residues. 212.04 ± 44.27 MT biochar could be produced from 517.82 MT crop residues in India. Biochar conversion of crop residues can address agriculture production, safe drinking water, livelihood, energy security and environmental protection. Soil amendment with biochar sequestrate about 376.11 ± 78.52 MT CO 2 e carbon and help retain about 1.66 ± 0.46 MT of soil nutrients. Also, crop residues derived biochar has an estimated market value of approximately $500 billion in India. Biochar applications in the cosmetics, pharma and chemical industries offer market and employment opportunities. This review discusses the impact of in-situ crop residue burning and its biochar conversion through slow pyrolysis as part of sustainable crop residue management. Also, biochar applications and socio-economic aspects of crop residues – biochar system has been deliberated to fulfil several sustainable development goals (SDGs). [Display omitted] • Impacts of crop residues in-situ firing in India were quantified and discussed. • Biochar conversion of crop residues for its strategic management was discussed. • Impact of pyrolysis process parameters on biochar yield & properties was reviewed. • Biochar as a conventional & upcoming value-added product was comprehensively analysed. • Crop residues – biochar system for the attainment of SDGs has been mapped. [ABSTRACT FROM AUTHOR]

• We model CO 2 source-sink matching for decarbonizing India's electricity. • Domestic and Middle East CO 2 storage sites are explored for optimized matching. • International matching with enhanced oil recovery enhances economic feasibility. • CO 2 shipping could expand the potential of CCUS in India's climate mitigation. India is the third largest CO 2 emitter in the world and the ascending trend has not shown clear signs of leveling off. Electricity generation is the most important contributing sector. This paper examines the role of CO 2 capture, utilization and storage (CCUS) in decarbonizing India's electricity. We build a source-sink matching optimization model and unlike previous research, include transport by ship to overseas CO 2 storage sites. We initialize the model with open-source data on power sector emissions and sinks to work out the least-cost solutions for achieving various CO 2 matching scenarios. CO 2 can be captured in fossil-fuel-fired power plants in India, while the utilization and storage could be either within or beyond the country's border. We assess the potential chain of shipping CO 2 to the Middle East for enhanced oil recovery and CO 2 storage. The economics of such international CCUS chains may affect the role of CCUS in India's decarbonization scenarios. We provide first order estimates of costs and conditions to make such a proposition attractive. The model is available with an open-source license and is customizable to include additional sources, onshore and overseas sinks, and shipping terminals. [ABSTRACT FROM AUTHOR]

• Review of methodologies for CO2 storage capacity estimation globally • Detailed assessment of CO2 storage capacities in different Indian basins • New classification scheme proposed based on 'storage prospectivity' of basins • CO2 storage capacities through EOR and ECBMR are 3.4 Gt and 3.7 Gt, respectively • Total theoretical CO2 storage capacity for India estimated at 395-614 Gt With rising carbon dioxide emissions and ambitious global targets for climate change mitigation, carbon sequestration has become one of the most promising carbon dioxide removal technologies. It can prove especially beneficial to an emerging country such as India, which must balance its rapid economic growth with a reduction in emissions. A detailed assessment of the cumulative storage capacity is necessary to facilitate the development of CO 2 storage pathways in India. Previous assessments for India have primarily estimated the theoretical storage capacity based on limited data. In this study, we have reviewed different methodologies for estimating storage capacities globally, and based on the most current data available, in a first, developed a systematic assessment for theoretical and effective CO 2 storage capacities for different geological formations in India. Four storage pathways with adequate potential have been identified: storage through CO 2 enhanced oil recovery (EOR), enhanced coalbed methane recovery (ECBMR), storage in deep saline aquifers, and basalt formations. The results indicate considerable potential for CO 2 storage in India, especially in saline aquifers (291 Gt) and basalt (97–316 Gt). Even though the storage capacity estimated through EOR (3.4 Gt) and ECBMR (3.7 Gt) is comparatively less, it is adequate to store emissions from nearby large point sources. These methods are also highly feasible due to the ready availability of infrastructure and extensive geological information about the basins involved. In addition, we have developed novel classification systems for different basins in India to represent their prospectivity for CO 2 storage. [ABSTRACT FROM AUTHOR]