October 2014 Archives

LED lighting: an accelerated learning curve?

News from Samsung (exiting the LED market) and Philips (spinning off their LED division) would seem to indicate rapid learning in the LED space. From Reuters:

Analysts say Samsung Electronics’ retreat reflects the growing competition from Chinese manufacturers even as demand for LED lighting remains strong. LED lamps last 10 times longer than fluorescent bulbs and 100 times longer than traditional incandescent tungsten filament bulbs.

“It appears that Samsung decided to fold the business because price competition was so fierce and there was not a lot of room for growth going forward,” said Seoul-based IM Investment analyst Lee Min-hee.

Philips said in September that it will spin off its lighting business to expand its higher-margin healthcare and consumer divisions. Two month earlier, Germany’s Osram Licht AG , which also makes LED lights, announced a cost-cutting plan that included nearly 8,000 job cuts.

Jason Snell put it best:

So, bad news for Samsung and other businesses betting on big margins for bulbs, but good news for everyone else.

BBC's Your life on earth

Put in a few facts about yourself — birthdate, gender and heights — and get an assortment of facts about how the world has changed since your arrival.

Some of mine:

  • Population has increased by ~2.8 billion; life expectancy is 8 years longer than when I was born
  • BBC projects Oil and Coal will run out by the time I’m 80. They estimate gas supplies will continue beyond my life, but not my children’s.

If you were born 4 years ago:

  • Population has increased ~327 million — 10 million more than the US!
  • While you’re on average (in the US) 3.3 ft tall, a coastal redwood would have grown ~5ft.

Kind of fun. I’d be interested to know a bit more about their data projections. They do offer a little bit of information, at least, about where the data came from.

via kottke

Introducing HAPIT

I’ve lead recent efforts to create a web-based tool to estimate the impacts of household air pollution interventions (like stoves, gas dissemination, etc) using methods based on what’s known about household air pollution and its contribution to the Global Burden of Disease. The project began as an Excel-based spreadsheet before moving to the web leveraging Shiny, R, and a fair amount of javascript. From the site:

HAPIT estimates and compares health benefits attributable to stove and/or fuel programs that reduce exposure to household air pollution (HAP) resulting from solid fuel use in traditional stoves in developing countries. HAPIT allows users to customize two scenarios based on locally gathered information relevant to their intervention, which is the recommended approach. This will normally require preliminary field work at the dissemination site to demonstrate pollution exposures before and after the intervention in a representative sample of households. If no local information is available, however, HAPIT contains conservative default values for four broad classes of household energy interventions based on the available literature — liquid fuels, chimney stoves, rocket stoves, and advanced combustion stoves. As each country’s health and HAP situation is different, HAPIT currently contains the background data necessary to conduct the analysis in 55 countries — those with more than 50% of households using solid fuels for cooking and China, which has a lower percentage of households using solid fuels for cooking, but a high number in absolute terms. See the drop down list on the left and the Info tab for more details.

HAPIT also estimates program cost-effectiveness in US dollars per averted DALY (disability-adjusted life year) based on the World Health Organization’s CHOICE methodology (see Info tab for more detail). It takes a financial accounting approach in that it 1) does not take into account the household costs such as fuel and health expenses or time spent cooking or acquiring fuel and 2) assumes that programs are covering the cost of fuel-based interventions (such as annual LPG costs per household). For custom scenarios, users can adjust the per-household maintenance or fuel cost based on the characteristics of their programs. All program costs should be entered in current US dollars.

There are a number of nice features of HAPIT, but one I’m particularly fond of is the customized, session-based pdf generated by clicking “Download Report.” HAPIT’s a work in progress and will continue to evolve in the coming months.

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snarglr is written & maintained by ajay pillarisetti



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