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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]

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]

There is a lack of studies on assessing long-term impacts of different sectors on shrinking global carbon budget. Present study focuses on assessing contribution of electric vehicles (EVs) with improving electricity grids' efficiency (EGs) and minimizing 'transmission and distribution' (T&D) losses in reducing carbon dioxide (CO 2) emissions and fulfilling emission targets for 2030 and 2050. Eleven different scenarios are articulated with estimated uncertainties for Mumbai Metropolitan Regions' (MMRs') passenger transportation using data extracted from MMR's Comprehensive Mobility Plan's transportation model. A novel methodology is developed to estimate local carbon budget targets from global targets between 2018 and 2050. The estimations indicate that carbon emissions in 'business as usual' scenario are 252%, 505%, and 55% above the targets for 2 °C, 1.5 °C, and Intended Nationally Determined Contributions (INDC), respectively. Study also shows that introducing EVs in MMR without simultaneously improving EGs will generate more net CO 2 emissions than BAU. EVs with EG and T&D improvements are not enough to meet the estimated targets. However, their combined contribution significantly reduces CO 2 emission by half and reaches peak emission by 2025 from post-half-century. • Developed a novel methodology to estimate local carbon budget. • Transport emissions assessment with electric vehicle, electricity grid (EG), and T&D losses. • Interventions are unable to achieve carbon budget targets of 2 °C, 1.5 °C, and INDC. • Electric vehicles are not suitable without improving EG efficiency, and T&D losses. [ABSTRACT FROM AUTHOR]

Enhancing and conserving carbon pools in vegetation is a major climate change mitigation strategy. The dynamics of carbon in terrestrial ecosystems depend on processes like photosynthesis, respiration, decomposition and combustion, anthropogenic activities like emission of greenhouse gases and climatic variations in rainfall and temperature, and is stored as biomass in different forms. The quantification of biomass is necessary to understand the productivity of forests, carbon sink and source dynamics and recommend ways to aid sequestration through supply side interventions like afforestation and demand side measures that check wood consumption. In this study, carbon sequestration based on the change in total carbon in two different scenarios using Markov chain and InVEST model is evaluated for the years 2000, 2018 and predicted for 2035. The results show that 1.351 Tg carbon has already been lost from 2000 to 2018 in the forest area of Sariska Tiger Reserve and another 0.107 Tg of carbon is expected to be lost in the predicted future, when we compare the land use land cover of the year 2035 with the present scenario. The local communities extract fuelwood by cutting down tree branches illegally, which leads to carbon loss into the atmosphere. The lower release of carbon in 2035 as compared to 2018 is because of forest management practices e.g., plantations done in the range Tehla-Talabberi, Sariska- Ganeshpura, Alwar buffer-Shoydanpura, Talvriksh-Manavaas, Akbarpur-Kalikhol, Ajabgarh-Jatwana. The study shows that the economic value of carbon lost from 2000 to 2018 is million $ 214.57 and if we see the economic value of the predicted year 2035, carbon sequestration is worth million $ 17.19. Outputs demonstrate the potential for restoration/reforestation and afforestation as the most practical carbon loss mitigation strategy and calls for improved access to cleaner energy sources where the renewable energy industry and government may pitch in. Image 1 • Markov chain and InVEST model were used to predict carbon sequestration. • Prediction maps revealed that open forest will be decreased in future. • Total carbon sequestration decreased 1.351 Tg during 2000–18. • It is predicted that −0.107 (Tg) carbon to be sequestered from 2018 to 35. [ABSTRACT FROM AUTHOR]