Contrasting chemical environments in summertime for atmospheric ozone across major Chinese industrial regions:The effectiveness of emission control strategies

The UKCA chemistry-climate model is used to quantify the differences in chemical environment for surface O3 for six major industrial regions across China in summer 2016. We first enhance the UKCA gas-phase chemistry scheme by incorporating reactive VOC tracers that are necessary to represent urban and regional-scale O3 photochemistry. We demonstrate that the model with the improved chemistry scheme captures the observed magnitudes and diurnal patterns of surface O3 concentrations across these regions well. Simulated O3 concentrations are highest in Beijing and Shijiazhuang on the North China Plain and in Chongqing, lower in Shanghai and Nanjing in the Yangtze River Delta, and lowest in Guangzhou in the Pearl River Delta despite the highest daytime O3 production rates in Guangzhou. NOx/VOC and H2O2/HNO3 ratios indicate that O3 production across all regions except Chongqing is VOC limited. We confirm this by constructing O3 response surfaces for each region changing NOx and VOC emissions and further contrast the effectiveness of measures to reduce surface O3 concentrations. In VOC limited regions, reducing NOx emissions by 20 % leads to a substantial O3 increase (11 %) in Shanghai. We find that reductions in NOx emissions alone of more than 70 % are required to decrease O3 concentrations across all regions. Reductions in VOC emissions alone of 20 % produce the largest decrease (- 11 %) in O3 levels in Shanghai and Guangzhou and the smallest decrease (- 1 %) in Chongqing. These responses are substantially different from those currently found in highly populated regions in other parts of the world, likely due to higher NOx emission levels in these Chinese regions. Our work provides an assessment of the effectiveness of emission control strategies to mitigate surface O3 pollution in these major industrial regions, and emphasizes that combined NOx and VOC emission controls play a pivotal role in effectively offsetting high O3 levels. It also demonstrates new capabilities in capturing regional air pollution that will permit this model to be used for future studies of regional air quality-climate interactions

Systematic Study of Dna Yield and Integrity in Bovine Long Bones

The purpose of this study was to identify a single source of bone that produced the most abundant, intact, and well-preserved deoxyribonucleic acid (DNA). The specific aim was approached through an experimental design using Bos indicus (the cow) femora presenting various degrees/modes of decomposition as sample material. Chips of bone were excised from seven locations on each femur including spongy and compact tissue types. DNA was isolated using procedures standard to functional forensic crime laboratories and subsequently quantified using Q-TAT and RT-qPCR assays. Furthermore, genomic degradation and the presence of PCR inhibitors for each sample was measured. Samples were successfully quantified using both Q-TAT and RT-qPCR technology and subsequently assessed for levels of degradation and PCR inhibition. Results from the Q-TAT assay suggested that spongy bone samples contained the presence of PCR inhibitors as evidenced by failed amplifications in 88% of reactions. Samples with failed amplification became ineligible for further analyses, making compact bone samples essentially the only tissues to produce data. The RT-qPCR assay amplified 97% of samples in the study allowing for a more comprehensive analysis of resulting data. Although not significant, compact bone samples yielded the most DNA and indicated low levels of genomic degradation and PCR inhibitors. Resulting data for compact bone samples was consistent across test groups, however variation in spongy bone was observed between bone groups. This finding suggests, that in general, compact bone is an ideal source for forensic analysis, however additional considerations can be made if spongy bone must be used.Forensic Science

Sensitivity of mid-19th century tropospheric ozone to atmospheric chemistry-vegetation interactions

We use an Earth-System model (HadGEM2-ES) to investigate the sensitivity of mid-19th century tropospheric ozone to vegetation distribution and atmospheric chemistry-vegetation interaction processes. We conduct model experiments to isolate the response of mid-19th century tropospheric ozone to vegetation cover changes between the 1860s and present-day and to CO2 induced changes in isoprene emissions and dry deposition over the same period. Changes in vegetation distribution and CO2 suppression of isoprene emissions between mid-19th century and present-day, lead to decreases in global isoprene emissions of 19% and 21% respectively. This results in increases in surface ozone over the continents of up to 2 ppbv and of 2-6 ppbv in the tropical upper troposphere. The effects of CO2 increases on suppression of isoprene emissions and suppression of dry deposition to vegetation are small compared with the effects of vegetation cover change. Assuming present-day climate in addition to present-day vegetation cover and atmospheric CO2 concentrations, leads to increases in surface ozone concentrations of up to 5 ppbv over the entire northern hemisphere (NH), and of up to 8 ppbv in the NH free troposphere, compared with a mid-19th century simulation. Ozone changes are dominated by: 1) the role of isoprene as an ozone sink in the low NOx mid-19th century at30 mosphere, and 2) the redistribution of NOx to remote regions and the free troposphere via PAN (peroxyacetyl nitrate) formed from isoprene oxidation. We estimate a tropospheric ozone radiative forcing of 0.264W m−2 and a sensitivity in ozone radiative forcing to mid-19th century to present-day vegetation cover change of -0.012W m−2

The TOMCAT global chemical transport model v1.6: description of chemical mechanism and model evaluation

This paper documents the tropospheric chemical mechanism scheme used in the TOMCAT 3-D chemical transport model. The current scheme includes a more detailed representation of hydrocarbon chemistry than previously included in the model, with the inclusion of the emission and oxidation of ethene, propene, butane, toluene and monoterpenes. The model is evaluated against a range of surface, balloon, aircraft and satellite measurements. The model is generally able to capture the main spatial and seasonal features of high and low concentrations of carbon monoxide (CO), ozone (O3), volatile organic compounds (VOCs) and reactive nitrogen. However, model biases are found in some species, some of which are common to chemistry models and some that are specific to TOMCAT and warrant further investigation. The most notable of these biases are (1) a negative bias in Northern Hemisphere (NH) winter and spring CO and a positive bias in Southern Hemisphere (SH) CO throughout the year, (2) a positive bias in NH O3 in summer and a negative bias at high latitudes during SH winter and (3) a negative bias in NH winter C2 and C3 alkanes and alkenes. TOMCAT global mean tropospheric hydroxyl radical (OH) concentrations are higher than estimates inferred from observations of methyl chloroform but similar to, or lower than, multi-model mean concentrations reported in recent model intercomparison studies. TOMCAT shows peak OH concentrations in the tropical lower troposphere, unlike other models which show peak concentrations in the tropical upper troposphere. This is likely to affect the lifetime and transport of important trace gases and warrants further investigation

Prediction of storm transfers and annual loads with data-based mechanistic models using high-frequency data

Excess nutrients in surface waters, such as phosphorus (P) from agriculture, result in poor water quality, with adverse effects on ecological health and costs for remediation. However, understanding and prediction of P transfers in catchments have been limited by inadequate data and over-parameterised models with high uncertainty. We show that, with high temporal resolution data, we are able to identify simple dynamic models that capture the P load dynamics in three contrasting agricultural catchments in the UK. For a flashy catchment, a linear, second-order (two pathways) model for discharge gave high simulation efficiencies for short-term storm sequences and was useful in highlighting uncertainties in out-of-bank flows. A model with nonlinear rainfall input was appropriate for predicting seasonal or annual cumulative P loads where antecedent conditions affected the catchment response. For second-order models, the time constant for the fast pathway varied between 2 and 15 h for all three catchments and for both discharge and P, confirming that high temporal resolution data are necessary to capture the dynamic responses in small catchments (10–50 km2/. The models led to a better understanding of the dominant nutrient transfer modes, which will be helpful in determining phosphorus transfers following changes in precipitation patterns in the future