Search

High ammonia (NH 3 ) and nitrogen oxide (NO x ) emissions are related to serious air pollution in urban areas and the negative impacts of excessive reactive nitrogen (N) deposition on many ecosystems. However, whether there is a relationship between N deposition rates and their sources with urbanization or not remains unclear in many areas. Here, we investigated the deposition rates of ammonium (NH 4 + ), nitrate (NO 3 - ), dissolved organic N, and water-insoluble particular N from July 2017 to June 2018 at two urban and two suburban sites in the Yangtze River Delta (YRD). The δ 15 N values of precipitation NH 4 + and NO 3 - were measured, and major sources were analyzed using a Bayesian isotope mixing model. Wet N deposition rates were higher in Yangzhou (developing city, 20.3-22.7 kg N ha -1  yr -1 ) than those in Nanjing (developed city, 19.4-20.5 kg N ha -1  yr -1 ), and were higher at urban sites (20.4-22.5 kg N ha -1  yr -1 ) than those at suburban sites (18.7-20.3 kg N ha -1  yr -1 ). δ 15 N values of precipitation NH 4 + increased with an increase in precipitation pH because ambient acidity affects the equilibrium isotope fractionation between NH 3 and NH 4 + and wet scavenging coefficients of NH 3 and particulate NH 4 + . For NH 4 + , combustion-related NH 3 sources (62%-65% with 5.5-6.4 kg N ha -1  yr -1 , including coal combustion, vehicle exhaust, and biomass burning) contributed more than volatilization NH 3 sources (35%-38% with 2.9-3.9 kg N ha -1  yr -1 , including fertilizer application and waste volatilization). For NO 3 - , non-fossil fuel NO x sources (50%-63% with 3.4-4.1 kg N ha -1  yr -1 , including biomass burning and microbial N cycle) were comparable to fossil fuel NO x sources (37%-50% with 2.4-3.4 kg N ha -1  yr -1 , including coal combustion and vehicle exhaust). This study evidenced high N deposition rates and the importance of combustion-related NH 3 emissions and non-fossil fuel NO x emissions in city areas of the YRD., Competing Interests: Declaration of competing interest The authors declare no competing financial interests., (Copyright © 2021. Published by Elsevier B.V.)

Analyzing the association between fine particulate matter (PM 2.5 ) pollution and socio-economic factors has become a major concern in public health. Since traditional analysis methods (such as correlation analysis and geographically weighted regression) cannot provide a full assessment of this relationship, the quantile regression method was applied to overcome such a limitation at different spatial scales in this study. The results indicated that merely 3% of the population and 2% of the Gross Domestic Product (GDP) occurred under an annually mean value of 35 μg/m³ in mainland China, and the highest population exposure to PM 2.5 was located in a lesser-known city named Dazhou in 2014. The analysis results at three spatial scales (grid-level, county-level, and city-level) demonstrated that the grid-level was the optimal spatial scale for analysis of socio-economic effects on exposure due to its tiny uncertainty, and the population exposure to PM 2.5 was positively related to GDP. An apparent upward trend of population exposure to PM 2.5 emerged at the 80th percentile GDP. For a 10 thousand yuan rise in GDP, population exposure to PM 2.5 increases by 1.05 person/km² at the 80th percentile, and 1.88 person/km 2 at the 95th percentile, respectively., Competing Interests: The authors declare no conflict of interest.