The Regional Impacts of Climate Change

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10.2.6.3. Pollution Hazards

Experiments by Hatakeyama et al. (1991) showed that the higher temperatures are, the faster ground-level ozone forms and the longer high concentrations of ozone last. Therefore, global warming would accelerate the photochemical reaction rates among chemical pollutants in the atmosphere, increasing oxidants in many urban areas. High levels of photochemical oxidants are associated with eye irritation, severe respiratory irritation, increased frequency of asthmatic attacks of susceptible persons, and decreased pulmonary functions (Ando, 1993).

10.3. Integrated Analysis of Potential Vulnerabilities and Impacts

10.3.1. North China

North China-including Beijing, Tianjin, the four provinces (Hebei, Henan, Shandong, Shanxi), parts of Anhui province, and parts of inner Mongolia-is an economic center of China. It also is a topographical and climatological entity. Its population is 371 million, and its area is 76.5 million ha, including 28.9 million ha of cultivated land. Because this region already is at risk from normal climate variability, it also is likely to be quite vulnerable to long-term secular shifts. The concept of regions at risk is used here to focus on four different managed ecosystems: water resources, agriculture, forests, and coastal zones.

10.3.1.1. Water Resources

Water resources in north China are sensitive and vulnerable to climate change because:

Trends of runoff for north China under four GCM scenarios are shown in Table 10-9. (At its lower reach, the Huanghe is elevated above its neighboring lands.) Both surface water and groundwater in north China seem to be quite sensitive to climatic variability, especially on the Huang-Hai plain, according to the model results. Under these scenarios, climate change will result in an additional shortfall of 0.15-1.4 billion m3 of water in the Jing-Jin-Tang subregion, which would cause economic losses of US$50-800 million (constant 1990 values) in a normal year and US$230-2,270 million in a very dry year.


Table 10-9: Runoff trends under four GCM scenarios.

GCM
Runoff Trends

LLNL (1) All decrease
UKMO-H3 Huanghe and area to its south decrease
Others increase
OSU-B1 Huaihe and area to its south increase
Others decrease slightly
GISS-G1 Huanghe, Liaohe, and Songhuajiang increase
Others decrease

(1) L. Gates, pers. comm. Note: Under the GCM scenarios, subregions of northern China have different ranges of runoff change: Jing-Jin-Tang (-16 to +3%); Huaihe River Basin (-15 to +8%); middle reaches of Yellow River Basin (-12 to -5%).





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