No abstract

PM2.5 pollution influences the population health and people's daily life. Because meteorological factors are main factor affecting the formation of PM2.5, the interaction between PM2.5 and meteorological factors needs to be better understood, both for air quality management and for PM2.5 projection. Here, we use a nonlinear state space method called the convergent cross mapping method to identify the complex coupling patterns between PM2.5 and meteorological factors in a plateau city: Xining. The results prove that PM2.5-meteorological coupling patterns change with seasons and PM2.5meteorological coupling patterns are fixed in spring, autumn and winter. In spring, there is a negative unidirectional effect from precipitation to PM2.5 and a negative bidirectional effect between relative humidity and PM2.5. In autumn, there are some negative bidirectional effects between PM2.5 and relative humidity, precipitation, and air pressure, while solar radiation has a positive bidirectional effect on PM2.5. In winter, there are negative bidirectional couplings between PM2.5 and wind speed and temperature and a positive bidirectional coupling between relative humidity and PM2.5. Furthermore, relative humidity is a consistent driving factor affecting PM2.5. Air quality managers may alleviate PM2.5 by increasing relative humidity. Thus, the results provide a meteorological means for improving air quality in plateau cities.

Maize is a major crop that is particularly sensitive to climate change. In addition, the extreme shortage of water resources threatens crop production. Thus, improving the effective utilization rate of water is an important problem to discuss. In this regard, we quantified the combined effects of meteorological conditions and irrigation levels during different growth stages on city-level maize yields in the Jing-Jin-Ji region from 1993 to 2019. The results show that the sowing period was affected by the minimum temperature, while the other growth stages were affected by the maximum temperature. At the ear stage of summer maize, when the effective irrigation rate reached the average level (52%), the inflection point of the total precipitation was 401.42 mm in the Jing-Jin-Ji region. When the total precipitation was higher than 401.42 mm, the summer maize yield decreased with the increasing total precipitation. Furthermore, the summer maize growth was significantly affected by drought at the seedling stage. At high effective irrigation rates and over long dry spells, as the mean daily temperature during dry spells increased, the maize yield easily increased. The increase in the effective irrigation rate can reverse the decrease in the summer maize yield. Moreover, the effective irrigation rate increased the maize yield with the increase rise in the temperature during longer dry spells, but the maize yield decreased with warmer temperatures during shorter dry spells. As such, our evaluation results will be useful for assessing food security and moving gradually toward achieving a water–energy–food nexus.

PM2.5 pollution influences the population health and people’s daily life. Because meteorological factors are main factor affecting the formation of PM2.5, the interaction between PM2.5 and meteorological factors needs to be better understood, both for air quality management and for PM2.5 projection. Here, we use a nonlinear state space method called the convergent cross mapping method to identify the complex coupling patterns between PM2.5 and meteorological factors in a plateau city: Xining. The results prove that PM2.5-meteorological coupling patterns change with seasons and PM2.5-meteorological coupling patterns are fixed in spring, autumn and winter. In spring, there is a negative unidirectional effect from precipitation to PM2.5 and a negative bidirectional effect between relative humidity and PM2.5. In autumn, there are some negative bidirectional effects between PM2.5 and relative humidity, precipitation, and air pressure, while solar radiation has a positive bidirectional effect on PM2.5. In winter, there are negative bidirectional couplings between PM2.5 and wind speed and temperature and a positive bidirectional coupling between relative humidity and PM2.5. Furthermore, relative humidity is a consistent driving factor affecting PM2.5. Air quality managers may alleviate PM2.5 by increasing relative humidity. Thus, the results provide a meteorological means for improving air quality in plateau cities.