cBalance has been engaging with Wipro, an Indian Information Technology Services Corporation, to estimate their GHG emissions from air travel since 2015.
The objective of the project has been to estimate GHG emissions from air travel, analyze Wipro’s flying patterns, estimate possible reductions in GHG emissions and recommend strategies to reduce GHG emissions.
The analysis was adhered to GHG Protocol’s Corporate Standard, accompanied by IPCC Guidelines 2006 to calculate airline specific emission factors (insert footnote)
Following the equation:
GHG Emissions = Activity Data x Emission Factor
Here, the Activity Data was the distance between Airport A to Airport B, calculated using great circle equation.
Emission factor was given in terms of kg CO2e / pax-km for each airline, distinguished based on whether the flight was International or Domestic and whether the flight was short, medium or long haul (this was determined based on the distance).
For FY 2014-2015 estimated GHG emissions were 170.1 thousand tonnes CO2e, with 1,269.8 million pax-km traveled across 5.0 lac flights
For FY 2015-2016 estimated GHG emissions were 152.9 thousand tonnes CO2e, with 1,134.4 million pax-km traveled across 4.7 lac flights
During these two cycle of analysis, other than estimating the GHG emissions from air travel, the major emphasis was on quantifying reduction potential and study reduction strategies. This was achieved by modeling two scenarios :
Best-In-Class Switch :
The goal of this scenario was to determine, for a given flight, the best airline in terms of emission factor ranking for its specified route. This helped us and Wipro quantify reduction potential just by switching over to a more efficient airline.
The estimated GHG emissions reduction from Best-In-Class switch for FY 2014-2015 were 59.9 thousand tonnes CO2e and for FY 2015-2016 were 36.9 thousand tonnes CO2e
Multi-stop to Non-stop Switch :
The goal of this scenario was to determine possible reductions in GHG emissions switching from a multi-stop flight to a non-stop flight.
The estimated GHG emissions reduction from Multi-stop to Non-stop switch for FY 2014-2015 were 19.4 thousand tonnes CO2e and for FY 2015-2016 were 11.7 thousand tonnes CO2e
In total, 79.3 thousand tonnes CO2e and 48.6 thousand tonnes CO2e reductions were estimated respectively for FY 2014-2015 and FY 2015-2016
A white paper titled Reducing Air Travel Emissions can be read here, where we have ranked airlines based on their GHG Emission Factor.
FY 2016-2017 & FY 2017-2018
For FY 2016-2017 estimated GHG emissions were 130.2 thousand tonnes CO2e, with 923.7 million pax-km traveled across 2.1 lac flights
For FY 2017-2018 estimated GHG emissions were 116.5 thousand tonnes CO2e, with 836.8 million pax-km traveled across 1.9 lac flights
Since the recommendations of flying the best-in-class airline, flying non-stop over multi-stop and choosing to travel via railways and/or use video calling services were already implemented, during these cycle only emission estimation was conducted on the business unit level.
For future development, the goal is to implement emissions and a financial budgeting system with respect to flying on a business unit level with the idea that it would create responsible air travel amongst employees.
Details on the Business Units wise emissions for FY 2016-2017 can be viewed here.
Furthermore, click here to view a comparison between Economy vs Business Class emissions between FY 2016-2017 and FY 2017-2018
Eliminate Carbon Emissions (ECE) Pvt. Ltd was contracted by the IPL Management upon the recommendation of the United Nations Environment Program (UNEP) to calculate the IPL’s annual carbon footprint (i.e. an inventory of the total greenhouse gas emissions – GHGs – that contribute to climate change, resulting from direct and indirect resource consumption through DLF IPL 2010’s annual operations).
The total carbon footprint of DLF IPL 2010 was estimated to be 42,264 tons CO2e. DLF IPL 2010’s Carbon Footprint can be thought of as requiring 169,055 trees to ‘neutralise’ its impact on climate change over a period of 20 years. This equates to approximately 2,818 trees per match.
The following activities comprise its carbon Footprint, in order of decreasing magnitude: travel and logistics (18,073 tons CO2e – 42.8%), stadium construction (9,932 tons CO2e – 23.5%), luxury hotel accommodation (9,927 tons CO2e – 23.5%) , food, beverage, and waste (1,201 tons CO2e – 2.8%) and electricity (996 tons CO2e – 2.4%). These results are displayed in the chart below:
Relative stakeholder contributions to the DLF IPL 2010 Carbon Footprint are: IPL/IMG Operations (9,861 tons CO2e – 23%), state association operations (12,861 tons CO2e – 30%), franchise operations (5,243 tons CO2e – 12%), spectator activities (14,300 tons CO2e – 35%). The following chart displays the results:
A majority of the carbon footprint of DLF IPL 2010 is the consequence of activities related to its contractors, while only 23% of the footprint is a direct consequence of direct IPL/IMG managed operations. It is imperative that footprint mitigation strategies account for this aspect of footprint distribution.
Spectators are the most significant stakeholders in terms of contribution to total carbon footprint. Private vehicular travel is the single largest contributing factor – responsible for 6,517 tons CO2e (45%) of the stadium spectator carbon footprint. It is imperative to address this disproportionately heavy reliance on private transport consumed for spectator travel when addressing the overall IPL carbon footprint.
TV viewership-related carbon footprint for DLF IPL 2010 was 358,039 tons CO2e and far outweighed the contributions of any other stakeholder or activity considered within the IPL carbon footprint boundary. This component of carbon footprint, and its root cause–large quantity of consumption of electricity through TV sets–needs to be addressed with greater emphasis on its analysis and mitigation through innovative strategies and interventions in future editions of the IPL.
The impact of stadium construction, one of the primary activities contributing significantly to the IPL footprint, needs to be mitigated by intervening and exploiting opportunities to infuse low-carbon and green architecture and construction practices as the cornerstone of future stadium construction activities at proposed stadiums that are intended for use by the IPL.
Best practice examples for a majority of stakeholder functions within the IPL have been identified and quantified and their initial feasibility assessed. Best practice benchmark replication across the IPL must be pursued as a potent and actionable strategy for optimizing the carbon footprint of the IPL prior to any resource and capital-intensive carbon footprint minimisation strategies.
All interventions must be accompanied by effective communication to all internal and external stakeholders. They must also be in consonance with a well thought-out greening strategy that aims not just at a carbon neutral IPL but sets itself the loftier target of an IPL that is a net carbon sink (an indicative road map is presented in Appendix H of the original report).
Best practice incentivisation through formal programs and its incorporation into contractual negotiations processes with all vendors, contractors and other relevant stakeholders is ascertained to be the most feasible ‘first step’ on the pathway to drastically reducing the carbon footprint of IPL in the forthcoming seasons. Central IPL support and nurturing of competitive franchise behavior through formal recognition of the ‘lowest carbon footprint’ or ‘greenest’ franchise is one illustrative example that may be expanded to envelop all aspects of IPL operations in future editions.
The carbon footprint determined as part of this project phase does not account for the entire life-cycle of the resources consumed and their comprehensive impact on Climate Change and ecology. Accounting for resource acquisition, processing, and disposal impacts could magnify the current extent manifold. A life-cycle analysis (LCA) of all primary resources consumed is essential to ascertain a more comprehensive carbon footprint that tends towards the true climate change impact of IPL. It is recommended that IPL 2011 be assessed on a LCA basis and that preparatory work for an LCA study be commissioned as part of the next phase of the project. The activity boundaries are outlined in the following table:
It is recommended that the IPL commission ECE to commence a comprehensive carbon footprint minimization analysis as part of a long-term ‘greening program’ (in fulfillment of its MOU with the UNEP’s Sports and Environment Unit) to identify means and alternatives for optimising and minimising its resource intensiveness.
Prior to minimising and offsetting the impact of future IPLs, it is recommended that the IPL commit to neutralise the impact of, as minimum, the four knock-out phase matches of DLF IPL 2010 (estimated to be 3,148 tons). While multiple options for offsetting are available in the conventional Carbon Offset market, the alternatives that result in equitable distribution of benefits to the grassroots stakeholder communities who are imperative to the project’s implementation are preferred as a more potent agent of social and environmental transformation.
Recycle Guru is an online platform helping citizens recycle their waste by enabling the informal recycling sector. It promotes the more sustainable use of resources to make communities healthier and cleaner and seeks to instill greater dignity in the recycling profession as well as into the perception of citizens who rely upon their services. Recycle Guru initiates the recycling process by collecting paper, plastic, metal, and glass wastes from households in Bangalore.
The motive of this project was to create a tool to estimate the Energy and GHG Emissions (or Carbon Footprint) conservation benefits of recycling versus the business-as-usual option for municipal waste management in India: landfilling. Achieved Energy saving is contextualized in terms of equivalent hour of usage of CFLs (compact fluorescent lamps), ceiling fans, laptop, washing machine, LCD TV, and the equivalent carbon sequestration capacity of trees.
Paper
Paper waste is categorized into following categories: paper sheets, newspaper inserts, newsprint, cardboard, and magazines. The Recycle Guru team observed the percentile contribution of each waste type as the following:
Paper sheets – 95%
Newspaper Inserts – 5%
Cardboard – 60%
Magazines – 40%
Life cycle emission (implies manufacturing from Virgin material, 0% recycled material) of each subcategory mentioned above is as follows:
Using the first order decay method, the emissions from disposal is estimated to be 1.725 kg CO2e/kg of waste. The total emissions saved from recycling is calculated by subtracting the life cycle emissions of the recycled material from the life cycle emissions of the virgin material and then adding the landfilling emissions. The results are displayed in the following table:
Plastic
Plastic waste consists of the following three categories: high value plastic (high density polyethylene), PET bottles (polyethylene terephthalate), low value plastic (low density polyethylene). The life cycle emissions from manufacturing for each subcategory are displayed in the table below.
Since Degradable Organic Carbon in plastic is almost negligible, methane generation from its disposal in landfills is considered to be Zero. To calculate the avoided emissions from recycling, the same formula as that for paper was used. The results are displayed in the following table:
Metal
Metal waste only contains one category comprising both aluminum and steel. As per the pattern observed so far, percentile contribution of aluminum and steel in metal waste is found to be 75% and 25%, respectively. The life cycle emissions (implies manufacturing from Virgin material, 0% recycled material) of each subcategory mentioned above is as follows:
Since degradable organic carbon in metal is almost negligible, methane generation from its disposal in landfills is considered to be zero. Emission savings for each category is estimated using the same equation as paper and plastic with the results displayed below.
Glass
Glass waste is categorized into the following categories: beer bottles (brand: Kingfisher), container glass, and generic glass. As observed so far by Recycle Guru team, there were many instances when beer bottles were counted in pieces instead of kilogram. Hence, carbon saving from beer bottles is estimated based on number of pieces taken for recycling. Kingfisher beer bottles (made up of glass) mostly come in 650ml and 330ml. These two
major categories are considered in modeling the carbon saving from piece of each type. Life cycle emission (implies manufacturing from virgin material, 0% recycled material) of each subcategory mentioned above is as follows:
Since degradable organic carbon in metal is almost negligible, methane generation from its disposal in landfills is considered to be zero. Emission savings for each category is estimated using the same equation as paper, plastic, and metal and the results are displayed in the following two tables.
As discussed above, the energy saving achieved is expressed in terms of following contexts: CFLs (compact fluorescent lamps), ceiling fans, laptop, washing machine, LCD TV, and the equivalent carbon sequestration capacity of trees. Electricity emission factor (including AT&T Loss) for Bengaluru city is 1.27 kgCO2e/kwh generated. The following table displays the results:
To find about the assumptions taken and the equations used, the original report can be read here.
The Orange County Foundation is a group of individuals who have experience in eco-friendly architecture and civil construction, and focus on sustainable urban development. The foundation has developed a self-sufficient green housing project at Pashan, Pune–the first of its kind–and is developing another green housing project, ‘Royal Orange County’ (ROC), at Rahatani Pune. This project involves eight multi-storied buildings, consisting a total of 353 residential flats. The ROC has adopted a number of sustainable and environment-friendly options, such as eco friendly architectural design buildings, renewable energy, waste management, wastewater management and low-carbon embodied construction and building materials.
Project Objectives:
Internal capacity building and skill development for the Orange County Foundation team to calculate the carbon footprint of their construction projects
License of authenticated database for India specific emission factors related to construction and building materials, electricity & energy, mobility, AFLOU, waste, and wastewater to map the environmental performance and sustainability impact of the Orange County Foundation’s projects
Life-cycle process mapping of the ROC construction to develop a toolkit for carbon ERP integration into their system
Carbon Footprinting of the design and construction phase of the ROC project
cBalance’s Roles:
Annual Enterprise-Use License for cBalance Carbon Emission Factor Database (CEFD) – cBalance authorized yearly subscription of the CEFD tool to the Orange County Foundation to map the carbon footprint of projects using India-specific emission factors of construction and building materials, energy, mobility, AFLOU, waste and wastewater.
Training to Orange County Foundation Team for Assessment of Carbon Footprint – cBalance team provided 16 hours extensive training to the Orange County Foundation team on the topic of carbon footprinting, life-cycle of a construction project and introduction to common carbon metrics for building operations. In addition, cBalance provided training on the CEFD tool and instructed how the CEFD can be helpful to choose sustainable and low-carbon activity or material alternatives.
Life-cycle Process Mapping and Toolkit Development for Carbon Footprint – The cBalance team visited the construction site and project office of the ROC. Through a site audit and interviews with project officers, cBalance mapped the activities related to the design and construction phase of the ROC. Thereafter, cBalance developed a toolkit that integrated into their existing system for mapping the life-cycle carbon footprint of the ROC and future projects.
Carbon Footprinting of Royal Orange County Residential Housing Project – The cBalance team collected data from the ROC on deforestation, electricity, fuels, and construction and building materials consumption of the construction phase of the ROC and calculated the construction phase carbon footprint using India-specific GHG emission factors. Finally, the cBalance team presented the carbon footprint analysis to the board of the Orange County Foundation.
Results:
Subscription to the CEFD and in-person training empowered Orange County Foundation team to:
calculate the carbon footprint of their projects using India-specific GHG emission factors
assess life-cycle environmental performance and sustainable impact of their projects
choose sustainable alternatives over conventional construction and building material
compare environmental performances of two different construction projects
create a baseline and frame future strategies to reduce the carbon footprint
The Orange County Foundation team calculated the carbon footprint of the ROC construction phase and successfully achieved a 15% reduction in GHG emissions compared with previous projects.
The above graph demonstrates this 15% reduction. Below, the GHG emissions from the construction phase categorized by scope are displayed. As is obvious, almost all of the emissions were Scope 3.
This blog post discusses the results of a report written in 2011 by Vivek Gilani and Dr. Amit Garg on the subject of the potential for improving the coal efficiency and GHG intensity of the steel sector in India.
Facts:
The domestic cola production target for 2011-12 was 554 mt. India added 1660 MW generation capacity in July of 2011 (all thermal power), and Indian plants exceeded their power generation target that month. Additionally, Coal India Ltd (CIL) reported a 64.06% rise in profit after tax (PAT) during the first quarter (April-June) of 2011-12.
India’s coal import in 2011-12 was predicted to be 137.03 mt, with some ports seeing huge increases in the amount of incoming imported coal. The import of coking coal through Paradip port on the eastern coast of India increased from 258,479 in June 2011 to 668,574 in July, an increase of 410,095 tons, or 159%. Imports of PCI coal through Vizag port in July 2011 stood at 113,467 tons, 86,764 tons more than the 26,703 tons imported in June 2011. And the imports of Low Ash Metallurgical (LAM) coke through Paradip port in the month of July 2011 rose sharply to 60,590 tons, compared with 6,000 tons in June 2011
Domestic mining has many environmental impacts, including the issue of land usage. 171 coal mining proposals involving 28,862 hectares of forest land are awaiting forestry clearance as of June 30, 2011. 44 projects of Coal India Ltd (CIL) stuck under Comprehensive Environment Pollution India (CEPI) norms introduced b they MoEF.
Question:
Can the most efficient users of coal in India’s steel sector help India:
increase its energy independence
meet its climate change commitments
and even save some forests?
Trends:
The following chart displays the GHG intensity of production in the Indian steel sector.
As is evident from the results, coking coal is the largest contributor at 40%, with coal being the second largest at 26%. Steam turbines and grid electricity, at 12%, were also significant.
The following table describes the GHG intensity of production in various steel companies throughout the sector.
The following table, on the other hand, depicts the coal efficiency and GHG intensity enhancement of Indian steel companies. In the years 2008-2010, they substantially exceeded their COP15 commitments regarding GHG mitigation.
The following graph displays the coal savings, GHG intensity reduction, and COP15 commitment opportunities of the steel sector for the same years.
The following chart displays the abatement potential for India’s steel sector for each measure, along with the necessary assumptions. Potentially, the 2030 projected emissions of 735 million tons of CO2e per year could be reduced to 573 million tons. Energy efficiency processes alone have an abatement potential of 73 million tons, shifting to scrap-based EAF has a potential of 21 million tons, and shifting to gas-based DRI, 17 million tons.
Measures:
Energy Efficiency can be improved through improving processes, namely sinter plant heat recovery and coal moisture control. Pulverized coal injection, coke dry quenching, and recovering waste heat also helps optimize energy use.
Savings can come from shifting fuel as well, substituting coke used in BF/BOF furnaces with fuel based on biomass (charcoal). Replacing 10% of coke as the primary blast furnace tool can also make a very sizable contribution.
Technology chances can have a big impact. One example is direct smelting, which removes the need for coking plants. (There are issues with these technologies that need to be resolved, of course). Another is scrap-based steel making, which uses 1/3 of the energy required by standard blast furnaces. The issue here is that if 10% of the total production moved to this system, 70% of India’s steel would need to be recycled, which would come with an economic cost. Lastly, gas-based direct reduced iron and cogeneration, i.e. recovering gas from the BOF/BF process and cleaning and using it for power generation, can also help to reduce emissions.
Energy independence and the Indian steel sector:
Coking coal prices were $129 a ton in 2009-10 but increased to $225 a ton in the second quarter beginning in July 2010. India has a very high dependency on Australia for coking coal and would need 2.4 billion tonnes of steel/yr by 2030, meaning India would need to import 40% of its coal needs.
Conclusion/way forward:
The best practice gap was achieved by the cement industry in its production from coal, increasing the GHG intensity ration from 13.4 to 15.7 in 3 years. Best practice technology (BPT) replication is achievable using off-the-shelf technologies in India. BPT replication in Steel Industry alone can yield 36 million tons of coal savings and reduce India’s imports drastically as well as help India achieve more than 100% of its GHG emissions commitment to COP15 (reducing the GHG intensity of GDP by 20%-25% by 2020). We are not anti-coal as fuel but, rather, a rational promoter of the roadmap to use India’s and the globe’s diminishing coal supplies more efficiently. The most pressing needs are process optimization technology sharing throughout the steel industry and active promotion and incentivization of efficient users of coal and low-GHG intensity steel on platforms such as coal junction and metal junction.
This blog post summarizes the carbon footprint calculation conducted by Eliminate Carbon Emissions Pvt. Ltd to measure the greenhouse gas emissions of the Neemrana Fort Palace Hotel (pictured below).
Goals and Scope:
The project goals were to determine with the great degree of accuracy possible the total resource consumption inventory, total carbon footprint, and the activity-differentiated carbon footprint of the Neemrana Fort Palace Hotel’s operations. The activity boundaries were categorized as Scope 1, 2, and 3 emissions, with the results displayed in the following table.
The stakeholders were defined as the primary realizer (Neemrana Fort) and the fruit jam production facility (Nainital). While many activities resulted in direct emissions (Scope 1), some resulted in indirect emissions through the generation of electricity (Scope 2), and the emissions caused by the production of goods used (Scope 3) must be included as well in a GHG inventory. The emissions of the latter group were calculated using the life cycle assessment.
Results:
The following table presents the extrapolated aggregated resource consumption inventory for the Neemrana Fort Palace Hotel.
This resource consumption resulted in a total of 3,282 tons CO2e of 0.145 tons CO2e per stay from the period of June 2009 to May 2010. The results, categorized by activity, are displayed below.
As is obvious from the results, the vast majority of the greenhouse gas emissions came from the generation of electricity (83.5%). While nothing else came close, the GHG emissions from water (2.3%), generator usage (2.5%) and meat and seafood (2.6%) were also significant. Food, beverage, and waste as a category contributed 6.2% of the total emissions. The same results are displayed in the pie chart below.
Conclusion:
With electricity generation being responsible for so much of the hotel’s GHG emissions, efforts to reduce these emissions should focus on reducing electricity consumption. Staff and guests can work together to use less electricity through a number of voluntary (or mandatory) measures.
Eliminate Carbon Emissions (ECE) Pvt. Ltd was contracted by the ‘ENGINEER 2010’ CORE to calculate their Carbon Footprint Calculation (i.e. an inventory of the total Greenhouse Gas Emissions that contribute to Climate Change), resulting from direct and indirect resource consumption through the annual technical fest’s operations. The subsequent report encompassed the first phase–‘Realise’– of the three-phase project comprising of Carbon Footprint Calculation (‘Realise’), Carbon Footprint Minimisation
(‘Minimise’) and Carbon Footprint Neutralisation (‘Neutralise’). This blog post discusses the findings of this report.
Project Goals and Scope:
The goals of the ‘Realise’ phase of the project were, to determine for ENGINEER 2010 the total resource consumption inventory, total carbon footprint, activity-differentiated annual carbon footprint, stakeholder-differentiated annual carbon footprint, and contextualization of total carbon footprint and carbon emissions intensity of stakeholder operations. The analysis of those aspects of operation would form a benchmark for assessing the impact of future members, and the aggregate and dissected carbon footprints were to be communicated in easily understandable terms. The results of this research were intended to serve as a diagnostic tool to help mitigate future carbon emissions.
Boundaries were defined in consultation with ENGINEER Management and involved two key-decision making areas, activities to be included and stakeholders to be considered. See previous blog post for discussion of protocols followed. More attention is paid to activities that are defined as ‘Key Source Categories, which are defined as those whose collective contribution account for 95% of the total footprint (when added incrementally in order of decreasing contribution). Activity boundaries categorized as Scope 1, 2, and 3 can be found in Table 1 on page 8 of the original report. Stakeholder boundaries were determined through consultation with the Client, and the results are displayed in the table below:
The following table presents the extent of LCA incorporated into the Emission Factors selected for the Carbon Footprint calculation.
Methodology:
Activity data was collected through periodic meetings with ENGINEER CORE representatives. Questionnaires were used to define relevant stakeholder groups and activities as well as to create an “activity vs. stakeholder mapping.” Electricity, water, and fuel consumption data was obtained from the previous year’s data to begin developing a pre-event estimate. To collect visitor travel activity data, detailed quantitative audience research was conducted to measure emissions, with a sample size of 10% of the expected audience being selected at random to answer a questionnaire.
Activities included within the footprint boundary were further differentiated into multiple activity sub-types. The results are displayed in table 4 on page 13 of the original report. Activity data was then multiplied by the appropriate GHG Emissions Factors developed for India, displayed in Appendix B of the same report.
Results:
The following table presents the extrapolated aggregated resource consumption inventory for ENGINEER 2010.
The total Carbon Footprint of ENGINEER 2010 for the activities presented in the first table and the stakeholders in the second is estimated to be 29.3 tons of CO2e. The following table and figure present the contributions to this total footprint differentiated across all activity groups.
As demonstrated here, travel and logistics was the largest contributor (11.2 tons CO2e–38.4%), and electricity was the second largest (9.6 tons CO2e–32.8%). Food, beverage, and waste was a distant third (4.4 tons CO2e–14.9%).
The following table and figure present the stakeholder contributions to the Carbon Footprint of all activities included within the footprint boundary.
The largest contribution is from activities related to the ENGINEER CORE (9.7 tons CO2e–33.0%).
For discussion of assumptions, data gaps, and limitations, read the original report.
Conclusion:
The Carbon Footprint estimate of 29.3 tons CO2e to serve a participant and visitor base of 4,233 persons leads to a per-participant served Carbon Footprint of approximately 6.9 kg CO2e. It must be noted, however, that the carbon efficiency of the participant stakeholder group is very high due to their use of mass transit systems and low reliance on private vehicular transport to the event. Moreover, guest accommodation was handled using in-house facilities. The elimination of luxury hotel accommodations had a drastic impact on the Carbon Footprint, as the arrangement allows for energy efficiency control and monitoring within the event premises that leads to much greater efficiency than is seen in the luxury hospitality industry in India.
In order to optimize resource and energy consumption, a few measures were recommended in the original report: Indoor temperatures can be raised by two degrees Celsius, lights can be switched off two hours per week, and home composting systems can be used for the disposal of biodegradable waste.
This blog post summarizes the carbon footprint calculation (i.e. an inventory of the total Greenhouse Gas Emissions (GHGs) that contribute to Climate Change resulting from direct and indirect resource consumption through event activities) of the IIM(A)’s CHAOS 2010 annual cultural festival, which was contracted to Eliminate Carbon Emissions Pvt. Ltd by the festival’s Organizing Committee.
Goals:
The project goals were to determine, with the great degree of accuracy possible, the following for CHAOS 2010:
Boundaries for the Carbon Footprint Calculation process were defined in consultation with CHAOS 2010 Management. Defining boundaries involved two key-decision making areas: activities to be included (i.e. defining a comprehensive yet manageable set of resources who’s consumption was to be inventoried) and stakeholders to be considered as part of the organization’s footprint (i.e. defining which sets of peoples/groups/functions are to be included within the footprint boundary).
Scope:
Since Carbon Footprint Reporting for events in India is not mandated by either the Indian Government or the United Nations Framework Convention for Climate Change (UNFCCC), and CHAOS 2010’s initiative to address its Climate Change Impacts is purely voluntary, there was no set of pre-established guidelines for boundary definition to be followed. Thus, the globally accepted methodologies for National GHG Emissions Reporting (adopted by India as part of the Kyoto Protocol) laid down by the IPCC (Inter Governmental Panel on Climate Change) as part of the 2006 Guidelines were used for guidance wherever appropriate. However, given the unique nature of this event, the overall methodology reflected a confluence of standard protocols and event-appropriate approaches which provide an accurate estimate of the Climate Change impact of a unique cultural and live-entertainment event, which CHAOS represents.
Activity Boundaries:
Contributing Directly to Carbon Footprint: Cooking Fuel Consumption, Vehicular Fuel Consumption (these are activities where an individual or business has direct control over the amount of activity and the emission coefficient through technological choices)
Contributing Indirectly to Carbon Footprint (Primary Importance): Electricity Consumption, Water Consumption (these are activities where an individual or business has direct control over the amount of activity but not the emission coefficient through technological choices)
Contributing Indirectly to Carbon Footprint (Secondary Importance): Transportation (Rail, Road, and Air Travel), Food & Beverage comprising of Meat, Seafood, Dairy, Rice, Alcoholic and Bottled Water/Soft Drink Beverage Consumption, Waste Generation, Plastic, Paper and Other Consumables (these are activities where an individual or business can be considered to not have direct control over the amount of activity nor the emission coefficient through technological choices)
Stakeholder Boundaries:
CHAOS 2010 Organization
Event Performers
Event Participants
Life-cycle Boundaries:
Methodology
The research methodology followed for the project centered around the idea of dissecting the event operations and disaggregating the consumption of resources to understand the consumption patterns ‘ground-up’. While this approach was more time-consuming, as opposed to tracking all activities through a ‘centralized’ approach, it helped construct a detailed footprint-map that would be invaluable as an analysis tool to identify stakeholder contributions to overall footprint. This data was then refined and scrutinized for inaccuracies when data appeared to be erroneous.
Results
The total carbon footprint of CHAOS 2010 for the activities and stakeholders presented previously is estimated to be 29.7 tons of CO2e.
Table 4 presents the contributions to the total carbon footprint differentiated by scope. Items identified as ‘not known’ represent data that was unavailable for analysis due to constraints encountered by data gathering personnel, and underlined quantities represent activities where consumption was estimated based on an assumed per-participant consumption quantity.
Figure 7 displays the percentage of overall GHG emissions per activity. Auto-rickshaw and flights were the two largest contributors at 29% and 21%, respectively.
Table 5 displays the GHG emissions per stakeholder. The participants, at 50%, were by far the largest contributors.
Figure 2 displays the same results in a pie chart.
Conclusions
Preemptively, Participant Travel and Waste Generation Footprints may be mitigated in future events through:
provision of mass-transit based systems, such as fuel-efficient or alternative fuel (CNG) buses, to transport participants from pre-determined nodal locations in the surrounding areas of IIM(A) to the event.
waste management principles centered around waste segregation, organic waste composting, and waste recycling must be adopted in conjunction with the rigorous participant awareness effort to ensure minimal waste is sent to landfills as an outcome of CHAOS.
Finally, based on the above analysis presented earlier, it is recommended that IIM(A) offset a significant percentage of the footprint of CHAOS 2010 (29.7 tons of CO2e) through ‘domestic’ action. It is recommended that IIM(A) review its monthly electricity consumption and set a achievable ‘percentage-reduction’ target for the first quarter during the new Academic Year beginning in mid-2010 to ‘offset’ at least 50% of the 19,192 units (i.e. 10,000 units).
This post summarizes an experimental design brief written by Vivek Gilani of cBalance. The project objective is to conduct testing of methane emissions for Organic Household Waste (OHW) to develop an emission factor for the purposes of Ecolabelling the Daily Dump’s Khamba Home-Composting Product. The methodology used for methane emissions measurement is the Status Flux Chamber Method as described in “Greenhouse gas emissions from home composting of organic household waste.”
The parameters for measurement are described in the table below:
The project time frame would consist of an active period of two to three weeks (with daily addition of OHW and 1 times/3 days mixing frequency) and a maturation period of three weeks (with no addition or mixing of OHW).
The schematics below depict how the experiment would be set up, allowing for adequate customization to accommodate the specific dimensions and design/operational principles of the earthen ‘Gamla’ product.
Data Analysis Protocol and Deliverables:
Methane concentrations will be analyzed using equipment equivalent to a photo acoustic gas monitor (INNOVA 1312, Lumasense Technologies) or Nondispersive Infrared Sensor (NDIR) sensor, which measures concentrations in real time and has high accuracy over a broad concentration range and with minimal re-calibration requirements during the project period of 6 weeks. The calibration shall be in the range of 0.03–50 ppmv for methane measurements.
The data deliverable for the project shall consist of Emissions Flux (ECH4) (in g/h) of CH4 plotted against time (for the entire duration of the project) where ECH4 is calculated using the following relationship:
ECH4 = dCCH4/dt * Vtotal,
Where Vtotal is the volume of the flux chamber plus the volume of the head space in the composting unit, which decreases over time as the unit is filled with waste.
The data should finally be converted to yield total methane emissions (mass basis) for the total composting cycle by integrating under the concentration vs. time curve for the entire project period (6 weeks)
Other notes:
The concentrations of gases inside the composting unit are expected to be elevated because of the build-up under the lid. Therefore, before measuring the emission of gases, the air in the composting units should be exchanged to start the measurement as close to ambient concentrations as possible.
The flux chamber, when placed on top of the composting unit, is expected to witness the emission of gases from the compost material, resulting in a linear increase of the gas concentration over the time period of measurement.
It is assumed that the entire volume of air over the waste is totally mixed during emission measurements. This should be ensured by mixing the air manually with a propeller.
The head space volume must be estimated for every emission measurement by measuring the height of the waste in the composting units.
The inlet to the gas measurement equipment (analyzer) should be equipped with a water filter (such as a membrane separator) to ensure that no moisture is transferred to the measuring
chamber.
The CH4 emissions are expected to be mostly affected by mixing the material. The emission of CH4 is anticipated to increase significantly after mixing the material but also decrease drastically to the original level within the first hour. This must be borne in mind when mixing the material and then replacing the static flux chamber swiftly to ensure measurement of gas concentration immediately after mixing.
We continue our blog with another post on the hotel industry, this time discussing Mumbai’s 5 star hotel Meluha the Fern, which commissioned cBalance to provide an analysis of its ecological footprint and consumption for the years of 2011-12. Meluha the Fern is a business hotel located in a hot and humid climatic zone (see our last blog post for more information on the different climatic zones) with 141 rooms. Laundry and waste water treatment (aerobic) is off-site, and the average room tafiff is Rs. 6400.
Greenhouse Gas Inventory:
As is evident from the graph, the vast majority of emissions come from electricity generation (84.45%). Laundry is the second largest source (3.88%), followed by PNG (3.48%, dairy (2.49%, and meat (2.27%).
The total footprint of the hotel was 4224.47 tCO2e, with 0.12 tCO2e per overnight stay, 0.34 tC02e per square meter, and 29.9 tCO2e per room per year.
Compared to its peers, Meluha the Fern is in the top 2 percentile for overall energy efficiency, top 4 percentile for hotels in the Hot & Humid climatic zone, top 9 percentile for all 5 star hotels, and top 2 percentile for all business hotels.
Results:
The total CO2e for the reporting period was 1263 tCO2e, with 919.34 tCO2e from guestrooms and 343.23 tCO2e from meetings. The carbon footprint per occupied room on a daily basis was 27.2 kgCO2e and 94.0 kgCO2e per area of meeting space.
The carbon footprint of fuel usage overwhelmingly came from PNG (69%), followed by LPG (18%) and diesel (13%). The cost was even more lopsided, with 96% from PNG and 2% each from LPG and diesel.
Carbon emissions was not the only performance indicator we analyzed, however; water consumption was also evaluated. 29069 kiloliters of water was used by Meluha the Fern (resulting in associated emissions of 16.1 tCO2e). Most of it came by tanker (56%), and domestic water (48%), flushing (25%), and the cooling towers (23%) were responsible for nearly all of its use.
cBalance also analyzed Meluha the Fern’s food waste, which totaled at 112.78 tonnes (resulting in 2.9 tCO2e emissions), 90% of which went to the piggeries, with the remaining 10% being composted.
Laundry is another significant contributor to Meluha the Fern’s ecological footprint. There were 639.96 tons of laundry with an associated emissions of 163.83 tCO2e (260 kgCO2e per ton). The tent card, however, helped save 2% of laundry, meaning 1460 kWh of electricity, 480 KL of water, 700 I of furnace oil, and 4.4 tCO2e GHG emissions per year.
The following table and graph illustrate Meluha the Fern’s solid waste management:
Most of the avoided emissions were from metals (44% and paper 42%).
Meluha the Fern has also achieved large savings from its water practices. The campus area is 1046 square meters, while the rainwater capture area is 3130.55 square meters. 7% of capture rainwater is reused (360 KL per year), and 93% of captured rainwater is recharged into the ground (4782 KL per year).
Energy savings result from Meluha the Fern’s choices of lighting equipment, as is shown by the following data:
Meluha the Fern also uses more sustainable forms of indoor cooling, with 10 split AC units (16 tonnes) and 50% of tonnage rated as 3 star equipment or above.
There are other areas as well where Meluha the Fern is able to save energy. 24% of the total pumping capacity comes from VFD pumps. Measures are taken to reduce refrigeration, 6% of the BUA is naturally lit, all of the windows are double-glazed, and all of the water pipes are insulated. 29% of the BUA is covered by BMS (building management systems), and the occupancy controlled area is 49% of the low traffic BUA area.
Some other notable sustainability measures included induction stoves for buffet counters, three self-cooking centers from Rational, a four bin method of trash segregation (at the source), no straws, paper napkins, or coasters, and glass bottles provided for water rather than bottled water (which aren’t filled unless asked for). Lastly, email usage is mandated and recycled paper is used for all stationary.
Other positives were that the data collection in housekeeping and engineering departments was excellent, and all staff members were very knowledgeable about sustainability initiatives within their departments.
Areas for improvement:
There were no sustainability initiatives involving guests, and the percentage of social development activities was very less (less than 1% of total man hours). There were not any norms for the use of organic food, either.
The following graph displays the coal savings, GHG intensity reduction, and COP15 commitment opportunities of the steel sector for the same years.
