Sources of Carbon Emissions

Exchange of carbon dioxide among the atmosphere, land surface and oceans is performed by humans, animals, plants and even microorganisms. With this, they are the ones responsible for both producing and absorbing carbon in the environment. Nature?s cycle of CO2 emission and removal was once balanced, however, the Industrial Revolution began and the carbon cycle started to go wrong. The fact is that human activities substantially contributed to the addition of CO2 in the atmosphere.

According to statistics gathered by the Department of Energy and Climate Change, carbon dioxide comprises 82% of UK?s greenhouse gas emissions in 2012. This makes carbon dioxide the main greenhouse gas contributing to the pollution and subsequent climate change in UK.

Types of Carbon Emissions

There are two types of carbon emissions ? direct and indirect. It is easier to measure the direct emissions of carbon dioxide, which includes the electricity and gas people use in their homes, the petrol burned in cars, distance of flights taken and other carbon emissions people are personally responsible for. Various tools are already available to measure direct emissions each day.

Indirect emissions, on the other hand, include the processes involved in manufacturing food and products and transporting them to users? doors. It is a bit difficult to accurately measure the amount of indirect emission.

Sources of Carbon Emissions

The sources of carbon emissions refer to the sectors of end-users that directly emit them. They include the energy, transport, business, residential, agriculture, waste management, industrial processes and public sectors. Let’s learn how these sources contribute carbon emissions to the environment.

Energy Supply

The power stations that burn coal, oil or gas to generate electricity hold the largest portion of the total carbon emissions. The carbon dioxide is emitted from boilers at the bottom of the chimney. The electricity, produced from the fossil fuel combustion, emits carbon as it is supplied to homes, commercial establishments and other energy users.

Transport

The second largest carbon-emitting source is the transport sector. This results from the fuels burned in diesel and petrol to propel cars, railways, shipping vehicles, aircraft support vehicles and aviation, transporting people and products from one place to another. The longer the distance travelled, the more fuel is used and the more carbon is emitted.

Business

This comprises carbon emissions from combustion in the industrial and commercial sectors, off-road machinery, air conditioning and refrigeration.

Residential

Heating houses and using electricity in the house, produce carbon dioxide. The same holds true to cooking and using garden machinery at home.

Agriculture

The agricultural sector also produces carbon dioxide from soils, livestock, immovable combustion sources and other machinery associated with agricultural activities.

Waste Management

Disposing of wastes to landfill sites, burning them and treating waste water also emit carbon dioxide and contributes to global warming.

Industrial Processes

The factories that manufacture and process products and food also release CO2 , especially those factories that manufacture steel and iron.

Public

Public sector buildings that generate power from fuel combustion also add to the list of carbon emission sources, from heating to other public energy needs.

Everybody needs energy and people burn fossil fuels to create it. Knowing how our energy use affects the environment, as a whole, enables us to take a step ahead towards achieving better climate.

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Migrating from CRM to Big Data

Big data moved to centre stage from being just another fad, and is being punted as the latest cure-all for information woes. It may well be, although like all transitions there are pitfalls. Denizon decided to highlight the major ones in the hope of fostering better understanding of what is involved.

Accurate data and interpretation of it have become increasingly critical. Ideas Laboratory reports that 84% of managers regard understanding their clients and predicting market trends essential, with accelerating demand for data savvy people the inevitable result. However Inc 5000 thinks many of them may have little idea of where to start. We should apply the lessons learned from when we implemented CRM because the dynamics are similar.

Be More Results Oriented

Denizon believes the key is focusing on the results we expect from Big Data first. Only then is it appropriate to apply our minds to the technology. By working the other way round we may end up with less than optimum solutions. We should understand the differences between options before committing to a choice, because it is expensive to switch software platforms in midstream. data lakes, hadoop, nosql, and graph databases all have their places, provided the solution you buy is scalable.

Clean Up Data First

The golden rule is not to automate anything before you understand it. Know the origin of your data, and if this is not reliable clean it up before you automate it. Big Data projects fail when executives become so enthused by results that they forget to ask themselves, ?Does this make sense in terms of what I expected??

Beware First Impressions

Big Data is just that. Many bits of information aggregated into averages and summaries. It does not make recommendations. It only prompts questions and what-if?s. Overlooking the need for the analytics that must follow can have you blindly relying on algorithms while setting your business sense aside.

Hire the Best Brains

Big Data?s competitive advantage depends on what human minds make with the processed information it spits out. This means tracing and affording creative talent able to make the shift from reactive analytics to proactive interaction with the data, and the customer decisions behind it.

If this provides a d?j? vu moment then you are not alone. Every iteration of the software revolution has seen vendors selling while the fish were running, and buyers clamouring for the opportunity. Decide what you want out first, use clean data, beware first impressions and get your analytics right. Then you are on the way to migrating successfully from CRM to Big Data.

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Becoming Nimble the Agile Project Management Way

In dictionary terms, ?agile? means ?able to move quickly and easily?. In project management terms, the definition is ?project management characterized by division of tasks into short work phases called ?sprints?, with frequent reassessments and adaptation of plans?. This technique is popular in software development but is also useful when rolling out other projects.

Managing the Seven Agile Development Phases

  • Stage 1: Vision. Define the software product in terms of how it will support the company vision and strategy, and what value it will provide the user. Customer satisfaction is of paramount value including accommodating user requirement changes.
  • Stage 2: Product Roadmap. Appoint a product owner responsible for liaising with the customer, business stakeholders and the development team. Task the owner with writing a high-level product description, creating a loose time frame and estimating effort for each phase.
  • Stage 3: Release Plan. Agile always looks ahead towards the benefits that will flow. Once agreed, the Product Road-map becomes the target deadline for delivery. With Vision, Road Map and Release Plan in place the next stage is to divide the project into manageable chunks, which may be parallel or serial.
  • Stage 4: Sprint Plans. Manage each of these phases as individual ?sprints?, with emphasis on speed and meeting targets. Before the development team starts working, make sure it agrees a common goal, identifies requirements and lists the tasks it will perform.
  • Stage 5: Daily Meetings. Meet with the development team each morning for a 15-minute review. Discuss what happened yesterday, identify and celebrate progress, and find a way to resolve or work around roadblocks. The goal is to get to alpha phase quickly. Nice-to-haves can be part of subsequent upgrades.
  • Stage 6: Sprint Review. When the phase of the project is complete, facilitate a sprint review with the team to confirm this. Invite the customer, business stakeholders and development team to a presentation where you demonstrate the project/ project phase that is implemented.
  • Stage 7: Sprint Retrospective. Call the team together again (the next day if possible) for a project review to discuss lessons learned. Focus on achievements and how to do even better next time. Document and implement process changes.

The Seven Agile Development Phases ? Conclusions and Thoughts

The Agile method is an excellent way of motivating project teams, achieving goals and building result-based communities. It is however, not a static system. The product owner must conduct regular, separate reviews with the customer too.

Data Replication

Medical Data Form

These days, not many companies can continue to operate once their entire computer system goes down. All the information needed in daily operations are stored in databases while the interfaces that make use of them all come in the form of software applications.

Software applications can be rapidly reinstalled and configured for as long as the necessary programs are available. Data, however, cannot be reconstructed as quickly even with hard copies available. It is therefore necessary to store your data in a replicated setup so that when one section goes down, operations can proceed without interruption.

For instance, if a category 5 hurricane renders your main office useless, you can simply rent workstations elsewhere, connect to the Internet and continue with your usual transactions for as long as data is readily accessible.

So how do we ensure the accessibility and reliability of your data? Here’s what we’ll do:

  • Activate data replication on your database management system. If your DBMS does not support replication, we’ll migrate all your data to one that does.
  • If absolutely necessary, we can allow modernised systems to run parallel to your legacy systems and prepare both for full modernisation when you’re ready.
  • Implement fail-over technologies where applicable to provide for automatic switching to a backup data server or network from one that has just failed.

We can also assist you with the following:

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