治理雾霾：不能测量就无法治理

在北京上一次遭遇史上最严重空气污染之后没几天，IBM就开始着手为城市打造更加强大的污染监测和预报体系，此举引发了广泛关注。蓝色巨人的中国研究实验室正联手北京环境保护局合作研发一款新系统。该公司还将与同样受到雾霾困扰的约翰内斯堡和新德里进行合作。

据IBM绿色地平线（Green Horizons）污染与可再生能源预报项目首席研究员亨德里克•哈曼介绍，北京现有的污染监测手段成本太高，精确度也不足。偌大的城市只有几十个监测站，尽管它们的测量十分准确，想要得出北京污染的详细情况却还不够。

作为这些监测站的补充，IBM和北京环境保护局打算建立由几百甚至几千个廉价、联网、易于维护、鞋盒大小的感应器组成的监测网络。

感应器获得的数据将通过整合天气模式，甚至空气化学反应的计算机模型进行分析，最终生成精确到1平方千米的72小时污染预报。

物联网和大数据的这种结合，正是城市智能化的缩影。

哈曼表示：“显而易见的是，如果不能测量，就无法治理。”

在交通堵塞和天气的问题上，这显然是真理，不过这里还有个疑问——城市“治理”污染究竟是什么意思？相较于摆脱污染，测量污染究竟有多重要？

表面上看，空气质量监测似乎只是一种反应式措施。当地的粒状物污染因为天气原因，每天都有所不同，哈曼甚至将严重的污染比作台风：“我面对台风无能为力，但我可以保护市民的安全。”在北京，保护市民免受污染就意味着学校停课放假，大型建筑调整进气口，政府发布警告建议人们减少室外活动。

当然，污染与台风不完全是一回事——首先，污染大部分是由人类造成的，人类也有一定的能力控制它，甚至每天都能控制。目前，北京的空气预警系统给予市政府很大的权力，比如停止建设，减少工厂作业（包括污染严重的火力发电站），限制车辆出行、爆竹燃放和烧烤活动。

这些限制措施会带来巨大的经济损失，哈曼博士表示，IBM研发的颗粒物污染预测会让政府的措施更具针对性——例如，如果关闭城市里某些区域的火力发电站对于减轻雾霾具有最大成效，那么就只需关闭这些发电站。

即便是短期关闭火电站，听起来也像是渡过雾霾高峰期的临时缓解措施，没有改变根本问题。不过，哈曼博士相信，通过基于情景的预报，以及公众意识的提高，更好的数据从长期上会改善污染状况。

该系统强大的建模能力，可以就某些项目提供更为详尽的成本和收益分析，例如升级公共交通工具的替代能源，加装烟囱过滤器，提高能源效率等。哈曼表示：“看看洛杉矶等城市（这些城市抗击雾霾问题已有数十年），随着对污染问题的测量和了解，他们逐步推行各种不同的措施。”

哈曼认为，更好的测量手段通过提供市民可以关注的污染基准，还能起到自下而上的监督作用。这能让城市居民个人的咳嗽和喘气变成一个群体关心的问题，换句话说，这些信息有助于将污染问题放在政治层面上解决。

不过在北京，官员还没有接受这个理念，公民时常难以获取污染数据信息。尽管中国已经有了采用其他能源的倾向，但依旧在很大程度上依赖火力发电。（财富中文网）

译者：严匡正

审校：任文科

Just days after Beijing’s worst day of air pollution in recent history, IBM is highlighting its efforts to build stronger pollution monitoring and forecasting systems for cities. Big Blue’s China Research Lab has been developing a new system with Beijing’s Environmental Protection Bureau, and on Wednesday announced partnerships with similarly smoggy cities including Johannesburg and Delhi.

According to Dr. Hendrik Hamann, a lead researcher with IBM’s Green Horizons pollution and renewable energy forecasting program, Beijing’s current pollution monitoring methods are both too costly and too imprecise. Only a few dozen monitoring stations are spread out over the huge city, and though they’re highly accurate, there aren’t enough of them to get a detailed picture. IBM IBM 5.04% and BEPB want to supplement those with a network of hundreds or even thousands of inexpensive, networked, low-maintenance sensors about the size of a shoebox.

Data from the sensors would be analyzed, using computer models incorporating weather patterns and even airborne chemical reactions, to produce 72-hour pollution forecasts detailed down to 1km-square areas.

It’s a melding of the Internet of things and big data that epitomizes the movement to smarter cities.

“Stating the obvious,” says Hamann, “What you can’t measure, you can’t manage.”

That’s certainly true of things like traffic congestion and local weather, but it demands the question—what exactly does it mean for a city to ‘manage’ pollution? And how important is it to measure it, compared to just getting rid of it?

On the surface, air quality monitoring can seem merely reactive. Local particulate pollution can spike from one day to the next due to weather patterns, and Hamann even compares a bad pollution day to a hurricane: “I can’t do anything about the hurricane, but I can protect the well-being of citizens.” In Beijing, protecting citizens against pollution means cancelling school for young kids, regulating air intake in big buildings, and government warnings against outdoor activities.

But of course, pollution isn’t quite like a hurricane—humans cause most of it in the first place, and they have some ability to control it, even day to day. Currently, Beijing’s air alert system gives the city broad powers to shut down construction and curtail industrial operations (including its nasty coal-fired power grid), and restrict driving, fireworks, and barbecues.

Those controls have substantial economic costs, and Dr. Hamann says the more granular forecasting IBM has developed would allow them to be more targeted—say, shutting down coal plants in only the parts of a city where it would do the most good.

Even temporarily shutting down coal plants, though, might sound like more short-term mitigation—a way to smooth out the smoggy peaks without changing the underlying problem. But Dr. Hamann believes better data will lead to longer-term improvements through a combination of scenario-based forecasting and public awareness.

Stronger modelling allows more detailed analysis of the costs and benefits of, say, upgrading public transportation to alternative fuels, adding smokestack filters, and increasing energy efficiency. “Look at places like . . . Los Angeles,” Hamann says, which battled its own smog problem for decades. “Through measurement, understanding of the problem, step by step, different actions were taken.”

Hamann thinks better measurement also works from the bottom up, by providing benchmarks that citizens can actually keep track of. That helps synthesize city dwellers’ individual coughs and wheezes into a collective project—in other words, information helps politicize pollution.

But in Beijing, officials haven’t embraced that idea, restricting access to information including the U.S. Embassy’s pollution readings. Though that mindset is improving, China is extremely dependent on coal for power. IBM’s super-accurate data won’t be able to fulfill its promise if those in charge prefer to keep things cloudy.