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Studying the spatiotemporal characteristics of air pollutants in urban agglomerations and their response factors will help to improve the quality of urban living. In combining air quality monitoring data and wavelet analysis from the Chengdu-Chongqing urban agglomeration (CCUA), this study assessed the spatiotemporal distribution characteristics and influential factors of air pollutants on daily, monthly and annual scales. The results showed that the concentration of air pollutants in the CCUA has decreased year by year, and air quality has improved. Except for O 3 , pollutants in autumn and winter were higher than those in summer. The spatial distribution of air pollutants was obvious distributed in Chengdu, Chongqing, Zigong and Dazhou. Pollution incidents were mainly concentrated in winter. The 6 air pollutants and air quality index (AQI) have dominant periods on multiple time scales. AQI showed positive coherence with PM 2.5 and PM 10 on multiple time scales, and obvious positive coherence with SO 2 , CO, NO 2 and O 3 in the short term scale. AQI was not strongly correlated with the fire point, but exhibited obvious negative coherence in the long term scale. In addition, AQI showed an obvious positive correlation with temperature and sunshine hours in short term, and a clear negative correlation with humidity and rainfall. The research results of this paper will provide a reference for pollution prevention and control in the CCUA. • Wavelet and IDW used to analysis air pollutants spatiotemporal characteristics. • Air pollutants shows obvious periodicity and mutation. • There is a certain correlation between AQI and wild burning sites. • Rainfall and humidity have a scrubbing effect on air pollutants. • The research results can provide policy basis to improve air quality in region. [ABSTRACT FROM AUTHOR]

Sustainability assessments are an increasingly common tool for measuring progress towards sustainable development. Despite their popularity, sustainability assessments and the indicators that compose them are said to have had little impact on the policy arena. In this paper we discuss four attributes that we contend will improve the use of sustainability assessments to guide decision making: non-compartmentalization, site specificity, built-in guidance for target setting, and ability to measure active sustainability. We present a novel assessment tool for wastewater treatment infrastructure that illustrates these attributes. The assessment is composed of two-dimensional indicators we call “burden to capacity” ratios, that reveal and quantify the local value of resources embodied in wastewater and treatment byproducts, and the tradeoffs between designing systems for disposal versus reuse. We apply the sustainability assessment framework to an existing treatment plant in Chengdu, China and discuss the results. [Copyright &y& Elsevier]