Greenhouse gases make high temps hotter in China

Greenhouse gases make high temps hotter in China


WASHINGTON (AP) — China, the world’s largest producer of carbon dioxide, is directly feeling the man-made heat of global warming, scientists conclude in the first study to link the burning of fossil fuels to one country’s rise in its daily temperature spikes.

China emits more of the greenhouse gas than the next two biggest carbon polluters — the U.S. and India — combined. And its emissions keep soaring by about 10 percent per year.

While other studies have linked averaged-out temperature increases in China and other countries to greenhouse gases, this research is the first to link the warmer daily hottest and coldest readings, or spikes.

Those spikes, which often occur in late afternoon and the early morning, are what scientists say most affect people’s health, plants and animals. People don’t notice changes in averages, but they feel it when the daily high is hotter or when it doesn’t cool off at night to let them recover from a sweltering day.

The study by Chinese and Canadian researchers found that just because of greenhouse gases, daytime highs rose 0.9 degree Celsius (1.7 degrees Fahrenheit) in the 46 years up to 2007. At night it was even worse: Because of greenhouse gases, the daily lows went up about 1.7 degrees Celsius (3 degrees Fahrenheit).

China is the world’s biggest producer and consumer of coal, which is the largest source of man-made carbon dioxide emissions. While the country has made huge investments in alternative energy such as wind, solar and nuclear in recent years, its heavy reliance on coal is unlikely to change any time soon.

About 90 percent of the temperature rise seen by the researchers could be traced directly to man-made greenhouse gases, the study said. Man-made greenhouse gases also include methane and nitrous oxide, but carbon dioxide is considered by far the biggest factor.

The study appeared online in late March in the peer-reviewed journal Geophysical Research Letters.

The study uses the accepted and traditional method that climate scientists employ to attribute a specific trend to man-made global warming or to rule it out as a cause.

Researchers ran computer simulations trying to replicate the observed increase in daily and nighttime high temperatures in China between 1961 and 2007. They first plugged in only natural forces — including solar variation — to try to get the heat increase. That didn’t produce it.

The only way the computer simulations came up with the increase in daily high and low temperatures that occurred was when the actual amounts of atmospheric heat-trapping greenhouse gases were included.

“It is way above what you would expect from normal fluctuations of climate,” study author Xuebin Zhang of the climate research division of Canada’s environmental agency said in a telephone interview. “It is quite clear and can be attributed to greenhouse gases.”

China did not become the largest emitter of greenhouse gases until 2007; for much of the period studied, it had a smaller economy. Because carbon dioxide stays in the atmosphere for about a century, China and its defenders maintain that the U.S. and other developed nations bear more responsibility for climate change.

Outside experts praised the research as using proper methods and making sense. An earlier study didn’t formally blame the proliferation of U.S. heat records to a rise in greenhouse gases but noted that they were increasing substantially with carbon dioxide pollution.

“The study is important because it formalizes what many scientists have been sensing as a gut instinct: that the increase in extreme heat that we’ve witnessed in recent decades, and especially in recent years, really cannot be dismissed as the vagaries of weather,” said Pennsylvania State University climate scientist Michael Mann.

China has rapidly grown from a nation of subsistence farmers at the end of the 1970s into the world’s second-largest economy behind the U.S., and the environmental costs of such change are often visible.

Beijing is no longer dominated by bicycles but by cars, and the skyline is barely visible at times because of thick pollution. More people are living in cities, buying air conditioners and other energy-hungry home electronics and consuming more energy for transportation and heating.

China passed the United States as the No. 1 carbon dioxide emitter about six years ago and “the gap is widening, it’s huge,” said Appalachian State University professor Gregg Marland, who helps track worldwide emissions for the U.S. Energy Department.

When developed countries around the world in 1997 agreed to limit their greenhouse gas emissions, developing countries, including China, were exempted.

U.S. Energy Department statistics say that China gets 70 percent of its energy from coal, compared with 20 percent in the United States. China is also a world leader in the production of cement, a process that also causes greenhouse emissions.


Scientists Decode Dreams With Brain Scans

Scientists Decode Dreams With Brain Scans

It It used to be that what happened in your dreams was your own little secret. But today scientists report for the first time that they’ve successfully decoded details of people’s dreams using brain scans.

Before you reach for your tin hat, you should know that the scientists managed this feat only with the full cooperation of their research subjects, and they only decoded dreams after the fact, not in real time. The thought police won’t be busting you for or whatever else you’ve been up to in your dreams.

All the same, the work is yet another impressive step for researchers interested in decoding mental states from brain activity, and it opens the door to a new way of studying dreaming, one of the most mysterious and fascinating aspects of the human experience.

In the first part of the new study, neuroscientist Yukiyasu Kamitani and colleagues at the Advanced Telecommunications Research Institute International in Kyoto, Japan monitored three young men as they tried to get some sleep inside an fMRI scanner while the machine monitored their brain activity. The researchers also monitored each volunteer’s brain activity with EEG electrodes, and when they saw an EEG signature indicative of dreaming, they woke him up to ask what he’d been dreaming about.

Technically speaking, this is what researchers call ”hypnagogic imagery,” the dream-like state that occurs as people fall asleep. In the interest of saving time, Kamitani and colleagues chose to study this type of imagery rather than the dreams that tend to occur during REM sleep later in the night. They woke up each subject at least 200 times over the course of several days to build up a database of dream reports.

In the second part of the experiment, Kamitani and colleagues developed a visual imagery decoder based on machine learning algorithms. They trained the decoder to classify patterns of brain activity recorded from the same three men while they were awake and watching a video montage of hundreds of images selected from several online databases. After the decoder for each person had been trained, the researchers could input a pattern of brain activity and have the decoder predict which image was most likely to have produced that pattern of brain activity.

But that much has been done before. Where Kamitani’s team went beyond previous work was in feeding the decoder patterns of brain activity collected while the subjects were dreaming. This enabled them to correctly identify objects the men had seen in their dreams, they report Apr. 4 in Science. Or rather, they could identify the type of object a subject had seen: it could predict that a man had dreamt about a car, not that he’d been cruising around in a Maserati. And the decoder only worked when the researchers gave it a pair of possible objects to chose from (whether it was a man or a chair, for example).

“Our dream decoding is still very primitive,” Kamitani said.

Decoding color, action, or emotion is also still beyond the scope of the technology, Kamitani says. Also, it only seems to work for imagery that occurred — at most — about 15 seconds before waking up.

Finally, the decoder is unique to each person. To decode the dreams of another person, the team would have to train up a new decoder by having that person view hundreds of images.

Even so, it’s remarkable that it works as well as it does, says neuroscientist Jack Gallant of the University of California, Berkeley and a pioneer of decoding mental states from brain scans. ”It took just a huge amount of non-glamorous work to do this, and they deserve big props for that,” Gallant said.

With refinements, Gallant says the method could be useful for studying the nature and function of dreams.

“There’s the classic question of when you dream are you actively generating these movies in your head, or is it that when you wake up you’re essentially confabulating it,” Gallant said. “What this shows you is there’s at least some correspondence between what the brain is doing during dreaming and what it’s doing when you’re awake.”

Kamitani is thinking about the possibilities too. ”One theory states that dreaming is for strengthening memory, but another theory states dreaming is for forgetting,” he said. “We could record the frequency of decoded dream contents for each memory item and see the correlation between the frequency and the memory performance.”