Air pollution is a complex issue that is difficult to communicate to most people. What causes air pollution? How does it affect our children’s cognitive development? What does air pollution have to do with rising temperatures?
Pallavi Pant is an air quality scientist who received her PhD in urban air quality in 2014. Today, she is a staff scientist at the Health Effects Institute in Boston. She is also Social Media Editor with the Journal of Exposure Science and Environmental Epidemiology, where she aims to communicate the journal’s work to a broader audience.
“But when it comes to communicating science, it’s vital to get the facts right. Young people like Pallavi—experts in their field with a passion to drive forward clear messages about air pollution, health and climate—are commendable in their ability to communicate the problems and how we can be part of the solution.”
This International Youth Day, themed “transforming education,” we asked Pant why, as a scientist, she feels compelled to tweet. How does she educate and bring complex messages to a non-scientific audience?
What influenced your decision to be a scientist, and is being a woman in this field a challenge?
I grew up in a household where curiosity was encouraged. I remember designing scientific experiments to test hypotheses as a kid with my friends. Throughout high school and college, I took steps towards a career in environmental science. In the early days, I wasn’t sure what aspect I would focus on; air pollution piqued my interest and I spent more time understanding it better. My personal experience living in Delhi—seeing the quality of air change over time—was another key contributing factor. Being a woman in science is fun and exciting, but also poses challenges. Occasionally, it has been difficult to deal with stereotypes that influence people’s interactions. In some instances, it is also about being safe—in the field working alone for example. But overall, I’ve had a good experience, and my mentors have been supportive.
Why do you feel it’s important to communicate science to a general audience?
Huge portions of important scientific research are still behind paywalls, and people are often unable to find accurate, reliable information, especially on digital media. Combined with the need for ‘bite-sized’ information, it is critical that scientists find ways to engage with the public, to dispel myths where they exist, and share useful information. After all, the goal for science is to help move towards a better future, isn’t it? During my PhD program, I started a knowledge platform—Air Quality in India—to publicize and communicate the latest science and policy developments on air pollution. I co-founded a similar effort for South Asia—Air South Asia. It is important that accurate, scientifically valid information is brought to the public. I also give public seminars on the topic of air pollution, and I answer queries from concerned individuals about sources of air pollution and possible impacts on human health. I engage with organizations that work directly with communities and point them towards trusted sources of information. On social media, I post curated content on air pollution.
The Journal of Exposure Science and Environmental Epidemiology is one of the first environmental journals to create its own social media platforms. What influenced this decision?
When I spoke with the journal editors, it was clear that they were trying to expand the reach and make the information accessible to a broad audience. I had some experience doing that, and this seemed to be an excellent opportunity to expand my skills too! We hope to disseminate new findings from research published in the journal on social media, and get others interested in the field of environmental health.
What is the biggest challenge you face in communicating air pollution science?
When we train as scientists, we are encouraged to speak in scientific terms. The first issue I encountered was to learn to take a minute and think about my choice of words, and how they would be interpreted by a particular audience. Air pollution science is often complex, and it is a hard task to explain the nuance of the science while making it engaging and interesting. For example, air pollutants can be primary [directly emitted] and secondary [formed in atmosphere from other pollutants], and control strategies are very different for both types of pollutants. Communicating this effectively can be challenging. Sometimes, it is only a matter of directing people to the right information. In other cases, some thinking is required. In all cases, the bottom line for me is to make the information relatable for the particular audience.
How do you hope to take your storytelling to a level where it can reach more people?
I am still learning ways to communicate science better, and weave data and stories together to generate meaningful narratives for people. This year, I am hoping to expand a large, open-source database on air pollution in India, set up a mentoring network for women in air quality in the South and continue working to expand the reach of the Journal of Exposure Science and Environmental Epidemiology.
Can you summarize the main threats of air pollution in 140 characters?
Air pollution impacts our health, environment & economy; we need to act both at personal & societal levels to improve the quality of air.
What is more disruptive with the AI: Its dark potentials or our (anti-Intellectual) Ignorance?
Throughout the most of human evolution both progress as well as its horizontal transmission was extremely slow, occasional and tedious a process. Well into the classic period of Alexander the Macedonian and his glorious Alexandrian library, the speed of our knowledge transfers – however moderate, analogue and conservative – was still always surpassing snaillike cycles of our breakthroughs.
When our sporadic breakthroughs finally turned to be faster than the velocity of their infrequent transmissions – that marked a point of our departure. Simply, our civilizations started to significantly differentiate from each other in their respective techno-agrarian, politico-military, ethno-religious and ideological, and economic setups. In the eve of grand discoveries, that very event transformed wars and famine from the low-impact and local, into the bigger and cross-continental.
Faster cycles of technological breakthroughs, patents and discoveries than their own transfers, primarily occurred on the Old continent. That occurrence, with all its reorganizational effects, radically reconfigured societies. It finally marked a birth of mighty European empires, their (liberal) schools and overall, lasting triumph of the western civilization.
For the past few centuries, we lived fear but dreamt hope – all for the sake of modern times. From WWI to www. Is this modernity of internet age, with all the suddenly reviled breakthroughs and their instant transmission, now harboring us in a bay of fairness, harmony and overall reconciliation? Was and will our history ever be on holiday? Thus, has our world ever been more than an idea? Shall we stop short at the Kantian word – a moral definition of imagined future, or continue to the Hobbesian realities and grasp for an objective, geopolitical definition of our common tomorrow?
The Agrarian age inevitably brought up the question of economic redistribution. Industrial age culminated on the question of political participation. The AI (Quantum physics, Nanorobotics and Bioinformatics) brings a new, yet underreported challenge: Human (physical and mental) powers might – far and wide, and rather soon – become obsolete. If/when so, a question of human irrelevance is next to ask.
Why is the AI like no technology ever before? Why re-visiting and re-thing spirituality matters …
If you believe that the above is yet another philosophical melodrama, an anemically played alarmism, mind this:
We will soon have to redefine what we consider as a life itself.
Less than a month ago (January 2020), the successful trials have been completed. Border between organic and inorganic, intrinsic and artificial is downed forever. The AI has it now all-in: quantum physics (along with quantum computing), nanorobotics, bioinformatics and organic tissue tailoring. Synthesis of all that is usually referred as xenobots(sorts of living robots) – biodegradable symbiotic nanorobots that exclusively rely on evolutionary (self-navigable) algorithms.
Although life is to be lived forward (with no backward looking), human retrospection is a biggest reservoir of insights. Of what makes us human.
Hence, what does our history of technology in relation to human development tell us so far?
Elaborating on a well-known argument of ‘defensive modernization’ of Fukuyama, it is evident that throughout the entire human history a technological drive was aimed to satisfy the security (and control) objective. It was rarely (if at all) driven by a desire to (gain a knowledge outside of convention, in order to) ease human existence, and to enhance human emancipation and liberation of societies at large. Thus, unless operationalized by the system, both intellectualism (human autonomy, mastery and purpose), and technological breakthroughs were traditionally felt and perceived as a threat. As a problem, not a solution.
Ok. But what has brought us (under) the AI today?
It was our acceptance. Of course, manufactured.
All cyber-social networks and related search engines are far away from what they are portrayed to be: a decentralized but unified intelligence, attracted by gravity of quality rather than navigated by force of a specific locality. (These networks were not introduced to promote and emancipate other cultures but to maintain and further strengthen supremacy of the dominant one.)
In no way they correspond with a neuroplasticity of physics of our consciousness. They only offer an answer to our anxieties – in which the fear from free time is the largest, since free time coupled with silence is our gate to creativity and self-reflection. In fact, the cyber-tools of these data-sponges primarily serve the predictability, efficiency, calculability and control purpose, and only then they serve everything else – as to be e.g. user-friendly and en mass service attractive.
To observe the new corrosive dynamics of social phenomenology between manipulative fetishization (probability) and self-trivialization (possibility), the cyber-social platforms – these dustbins of human empathy in the muddy suburbs of consciousness – are particularly interesting.
This is how the human presence eliminating technologies have been introduced to and accepted by us.
How did we reflect – in our past – on new social dynamics created by the deployment of new technologies?
Aegean theater of the Antique Greece was the place of astonishing revelations and intellectual excellence – a remarkable density and proximity, not surpassed up to our age. All we know about science, philosophy, sports, arts, culture and entertainment, stars and earth has been postulated, explored and examined then and there. Simply, it was a time and place of triumph of human consciousness, pure reasoning and sparkling thought. However, neither Euclid, Anaximander, Heraclites, Hippocrates (both of Chios, and of Cos), Socrates, Archimedes, Ptolemy, Democritus, Plato, Pythagoras, Diogenes, Aristotle, Empedocles, Conon, Eratosthenes nor any of dozens of other brilliant ancient Greek minds did ever refer by a word, by a single sentence to something which was their everyday life, something they saw literally on every corner along their entire lives. It was an immoral, unjust, notoriously brutal and oppressive slavery system that powered the Antique state. (Slaves have not been even attributed as humans, but rather as the ‘phonic tools/tools able to speak’.) This myopia, this absence of critical reference on the obvious and omnipresent is a historic message – highly disturbing, self-telling and quite a warning.
Why is the AI like no technology ever before?
Ask google, you see that I am busy messaging right now!
They promised us Martian colonies; instead, we got Facebook
The advent of the digitization changes the values of the society, especially as an apparatus of power, not as a real benefit to humanity.
Everyone talks about digitalization. When I browse the science and technology section in newspapers, I mostly find articles on smartphones, clouds, and social media. And I realize that the entertainment industry has become the technological progress engine nowadays.
For purposes of illustration: by 2019, California invested around 75 billion USD in venture capital, more than a half of it across the US, distributed between more than 2,300 startups. That is substantial. But if you take a closer look, the picture changes. More than a half of that goes into software development, with only about 20 percent allocated for life sciences and almost nothing for significant engineering. The buzz words are always the same: “cloud” something, “smart” something, “AI” something, “blockchain” something. In the meantime, the more aloof the claim, the higher the probability of funding, even if the real innovative benefit to humanity is negligible.
The situation is not better in other technology centers, including those in Europe. So in the end, we have cases like Theranos which turn out to be fraud machines on a large scale. We have the Binary Options scam startups in Tel Aviv which plundered the savings of people from half a continent. Or Wirecard in Germany suspected of operating one of the largest cloud platforms for money laundering.
If not based on a robust fraudulent scheme, the business models of such “cloud” something, “smart” something, “AI” something, “blockchain” something companies are actually ailing right from the start. Most users are not willing to pay money to use their platforms. That’s why the tech giants have come up with an idea: they pretend to believe in the dream of free use –and users pay with their private data.
Just imagine that we are back in the year 1990 when sending letters and making phone calls were still relatively expensive matters. The representative of a new telecommunications company stands at your door and says: “We have a super offer for you. You will never have to pay for long-distance calls again, we will also deliver every letter for free. But we will record everything you say or write. Furthermore, we reserve the right to analyze this information, share it with others, sell it, and besides–if we don’t like specific content –to delete it.” It’s clear what you would have said or done at the time to such a representative.
Today, we embrace the digital monitoring of society because we see this as a new normality. The sin was committed in 2004 when Google went public after the dotcom bubble burst. Even in the 1990s, search engines and social networks were still underpinned by the best intentions. They were meant to connect people, help share knowledge, create common grounds, and make money. It was about indexing websites while preserving the informational self-determination of the individual. Then it became clear that little money could be earned that way. And so began the indexing –the profiling – of users, i.e., people of flesh and blood.
The new tech companies collect all the data about our searching, writing, reading, walking, breathing, eating, paying, liking, loving, disliking, laughing, and purchasing behavior. This is called the Big Data. They can use that information to track us and sell us things. Or to monitor our thoughts and sell us lies. Or to surveil our opinion and manipulate us. Or they can resell the data and the analyzed profiles to third parties, including governmental organizations and political parties.
Artificial Intelligence plays a dominant role in this user profiling, monitoring, and surveillance business, since it delivers the techniques for it. Some computer scientists involved in Artificial Intelligence development enthusiastically say: “When computational learning ability meets large amounts of data, the quantity should one day turn into quality.” In other words, intelligence that learns on its own is actually created. Maybe so, but we are a long way from that.
Neural networks in AI remain classification and correlation machines. They detect patterns in data, for example, faces on billions of pictures. From such patterns, findings can be derived which, in turn, can be interpreted and used by humans. Yet, first of all, this has nothing to do with intelligence in the genuine sense of the word. It has nothing to do with the ability of an organism to independently create a model and to make decisions to adapt and thus to survive on its basis. If still more computing power meets more data, then we get better correlations, better pattern recognition, but not intelligence.
In 2012, the world’s fastest supercomputer was running at the Lawrence Livermore National Lab. It simulated a neural network with the complexity of a human brain with 530 billion neurons and 137 trillion synapses. The machine required eight megawatts of power but was 1,500 times slower than a human brain. Consequently, it would need 12 gigawatts to simulate an average human brain in real-time (let us say, that of an acumen of Omar Simpson). That is the power of about 15 to 20 nuclear reactors or 100 coal-fired power plants. Greta Thunberg will be glad to hear it! We will never, ever create artificial intelligence with the existing computer architectures.
The tech giants, from Facebook to Google, and the technological centers pursuing the buzz of the “cloud” something, “smart” something, “AI” something, “blockchain” something are making our lives difficult with their practices. The Silicon Valley and other comparable innovation centers promised us Martian and Moon colonies. They promised us luxurious interplanetary vessels populated with androids to do our housework and sexy cyborgs to entertain us with brilliant conversations. Instead, we received smartphones with preinstalled Facebook apps or other similar social media platforms. And in certain cases we got industrial robots that are taking away our jobs. Or algorithms running on supercomputers that automatically invest our hard-earned pensions into the technological innovation of the “somethings”. Or computational propaganda bots that trigger chain reactions of posts in social networks by publishing messages of ideology or hate or investment advice. The list of innovations that we got is long.
The upside is that if Facebook would vanish from the face of the earth tomorrow, what would be the consequences for humanity? None! Except for the tears of loneliness flowing on empty screens among social media addicts. But one thing is clear: the advent of the digitization changes the values of the society and the quality of life as much as the advent of plastic did. Its long-term benefits are ambiguous. The responsibility for these innovations is enormous, certainly, not as a “technical means”, but as an instrument of power and power itself .It is through the culture of digitization that the spirit of a new power will manifest itself. There is no doubt (you can already judge by the early signs today) that digitization will be authoritarian and repressive like no other culture in the world.
Can China electrify all new passenger cars by 2030?
electric vehicle industry is entering a new phase of accelerating development,
President Xi Jinping wrote in a congratulatory message to participants of a new energy
vehicle conference in early July. In 2018, China sold almost as many electric vehicles as
the rest of the world combined. At the same event, the chairman of Chinese
electric vehicle giant BYD upped the ante, challenging China to electrify all passenger vehicles
New energy vehicle sales are booming, but they still only amounted to 2.5% of car sales in China in 2018. Could all sales feasibly be electric within the next decade?
A recent report from the Innovation Centre for
Energy and Transportation (iCET) made the first public proposal of a timeline
for the phaseout of petrol and diesel vehicles across China. According to the
Beijing-based thinktank, 2030 is premature, but an entire phaseout could be
possible by 2040. However, the report also highlights significant uncertainties
ahead, including whether consumer appetite for electric vehicles will wane when
government subsidies are cut.
Why phase out traditional vehicles?
Starting in 2016, regions and countries around the world began proposing an end to driving as we know it. China’s vice minister of industry and information technology made waves when he announced in 2017 that China, the world’s largest car market for the past decade, was researching a phaseout of petrol and diesel vehicles.
The news followed a steady drumbeat of policies supporting the growth of China’s new energy vehicle industry in recent years. From generous government subsidies to driving restriction exceptions in China’s congested cities, the government has been coaxing the industry along.
much to gain from phasing out all petrol and diesel vehicles. For one, the
country relies on imports to meet 70% of its crude oil demand, 42% of which is consumed by vehicles. Petrol and
diesel cars also have a major impact on public health. They are among the main perpetrators of air pollution in many of China’s
cities. As car ownership has climbed, increasing oil use has also contributed to China’s rising greenhouse gas
With solar panels and wind turbines, China used subsidies to build companies that now dominate the industries worldwide. The burgeoning electric vehicle market presents a similar opportunity.
Is a phaseout possible?
Hainan, the island province in China’s south, has emerged as a green pioneer in recent years. In a plan released in March this year, it became the first region in China to set an official date for the phaseout of petrol and diesel vehicles.
Hainan has its sights set on 2030, but the rest of the country is unlikely to meet that deadline according to iCET’s report. The group built a model based on China’s automobile industry trends, national policies and oil consumption under a scenario of limiting global warming to under 2C, and proposed a phaseout timetable accordingly. The timetable states that smaller petrol and diesel passenger vehicles will be phased out between 2020 and 2040. Larger “commercial vehicles”, such as buses and trucks, will follow, so that all petrol and diesel vehicles are phased out by 2050.
The study proposes an incremental phaseout based on the type of vehicle and region. The largest cities that already have strong electric vehicle markets are prioritised along with cities suffering the most from pollution, while relatively underdeveloped regions are given more time to make the transition. Taking the lead will be government-owned vehicle fleets, followed by private vehicles, which will allow some time for costs to come down further for alternative vehicle technologies. The majority of passenger vehicles will be replaced by new energy vehicles and non plug-in hybrids (like the Toyota Prius) according to the study.
Taiyuan, an industrial city in west China, has already demonstrated this model by electrifying its taxi fleet. Shenzhen followed suit this year. However, Li Wanli, formerly of the Ministry of Industry and Information Technology, commented at the report launch: “I personally think the proposed timetable is too early and tight for privately owned vehicles.”
He also cautioned that the study’s suggested approach may pose problems. Citing fuel efficiency standards being rolled out regionally right now, he said the piecemeal approach has caused headaches for manufacturers and is a case to learn from.
Although the study’s timetable aligns with current policies and projections, the authors elaborate that several uncertainties could influence China’s path. The electric vehicle industry is in the midst of a major transition. Subsidies have long been boosting sales, accounting for 20-35% of the take-home sale price for manufacturers in 2016. Now, the government has decided to wean the industry off the handouts, likely entirely by 2020.
This shift could dampen consumer appetite. Projections show that electric vehicles could reach price parity with petrol and diesel vehicles by 2030, but for now they will likely remain out of reach for many Chinese buyers without government support. The Tesla Model 3, for instance, is being advertised as a vehicle for the mass market. But its price tag is still about US$15,000 above the average car in China.
Whether enough alternative cars can be produced is also moot. Production of new energy vehicles is slightly above sales in China, but even at over one million sales in 2018, it is dwarfed by the market for conventional vehicle. To encourage production, this year China is introducing a national production policy for large manufacturers. The system is slightly more complex than a pure quota, but it essentially requires automakers to meet production targets for 2019 and 2020 or buy credits from overperforming companies. The policy is expected to double new energy vehicles’ share of sales, according to Bloomberg New Energy Finance, but no quota has been set for after 2020.
Whether infrastructure can keep up with the phaseout is also a looming question. Building out enough charging stations to supply a rapidly expanding electric vehicle fleet is a government priority, and an unprecedented challenge. The power grid may also struggle to keep up with charging if demand is not timed intelligently. A Natural Resources Defense Council (NRDC) study found that peak load on the grid could increase 58% by 2030.
Environmental pros and cons
The iCET study finds that greenhouse gases and air pollution would be reduced significantly if their timetable is followed. A study by the China Automobile Technology Research Centre found that phasing out petrol and diesel vehicles would lead to a 41% drop in nitrogen oxide and a 35% drop in particulate matter emissions in 2050, compared to a 2017 baseline. Based on the iCET study, end-user greenhouse gas emissions would fall 51% in 2040 and 77% in 2050 while lifecycle emissions (including from electricity generation) would fall 55% in 2050.
However, electric vehicles are not without their own environmental hazards. Battery supply in particular has raised red flags. Currently, battery recycling remains very low due to there being diverse battery types and an unwillingness from recyclers to take responsibility for safety risks. The iCET study warns that if a better recycling system is not established, lithium, cobalt and manganese in the batteries could cause significant damage to public health and the environment. Dealing with this blockage in the electric vehicle lifecycle could slow down the rollout, the authors argue.
Setting a date
The government has set a number of long-term targets for new energy vehicle production. The most ambitious is for them to account for 40% of car sales by 2030. Will China ratchet up the pace by setting a phaseout target on top of that?
Hainan has already fired the starting gun. However, its vehicle market is relatively small (the province has about one sixth as many cars as Beijing) so it will not be as significant an undertaking there. A Caixin article suggests that Beijing might be a good candidate to follow Hainan’s example as it has led in the establishment of other new energy vehicle policies in the past.
At the report release, Wang Baixia, one of the drafters of Hainan’s phaseout plan, said having a target would send a strong signal: “A timetable is still needed, for the government and companies, everyone needs such a timetable (…) this long-term expectation is very important.”
The government is working on a 15-year new energy vehicle development plan, which may provide further clarity on its phaseout plans.
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